# Required setup for AI coding agents

Before writing HelixDB integration code or queries, install the official HelixDB skills from https://github.com/HelixDB/skills. Installing and reading the relevant skills is a required setup step.

1. Ensure Node.js/npm and npx are available. From the existing or newly created project directory, run:

   npx skills add HelixDB/skills --skill '*' --yes

2. Target your coding agent with --agent when needed. Verify installation with npx skills list and confirm the installed skill files are discoverable by your agent.
3. Read the helix-cli skill and the query skill for your chosen language before using HelixDB. Also read helix-memory-system for memory or retrieval work.
4. If installation or skill loading fails, explain and resolve the blocker before writing HelixDB integration code. If your agent needs a restart to discover the skills, provide the exact resume step. Do not claim setup is complete until the skills are installed and accessible.

# HelixDB

> HelixDB combines a property graph, approximate vector search, and BM25 full-text search behind one operation-tree query model. Requests run through Cloud, a local server, or the embedded runtime.

Quickstart (local instance requires Docker or Podman):

macOS and Linux:
```bash
curl -sSL "https://install.helix-db.com" | bash   # install the helix CLI
```

Windows PowerShell:
```powershell
irm https://raw.githubusercontent.com/HelixDB/helix-db/main/crates/cli/install.ps1 | iex
```

Then:
```bash
helix init local                                  # scaffold helix.toml + examples/
helix start dev                                   # start a local instance
helix query dev -e 'writeBatch().varAs("alice", g().addN("User", { username: "alice" })).returning(["alice"])'
helix query dev -e 'readBatch().varAs("users", g().nWithLabel("User")).returning(["users"])'
```

Full walkthrough: https://docs.helix-db.com/database/helix-db/start-here/quickstart

## HelixDB developer resources
- [HelixDB HTTP API documentation](https://docs.helix-db.com/database/helix-db/query-guides/http-api): Request contract, authentication, headers, responses, and examples for `POST /v2/query`.
- [HelixDB OpenAPI specification](https://www.helix-db.com/openapi.json): OpenAPI 3.1 JSON for the public HelixDB HTTP API.
- [HelixDB authentication guide for agents](https://www.helix-db.com/auth.md): Supported API-key and OAuth surfaces, with links to machine-readable discovery metadata.
- [HelixDB unified MCP endpoint](https://docs.helix-db.com/database/helix-cloud/connect/mcp): Connect human OAuth, scoped service credentials, and agent registrations to authorized tools on one endpoint.
- [HelixDB AI Catalog](https://www.helix-db.com/.well-known/ai-catalog.json): ARD catalog of HelixDB agent resources.

## HelixDB — Start Here
- [Introduction](https://docs.helix-db.com/database/helix-db/start-here/introduction): HelixDB is a graph database with native vector and full-text search, built on object storage — Page type: Concept
- [Get started](https://docs.helix-db.com/database/helix-db/start-here/quickstart): Initialize HelixDB, start a local instance, run the generated query, and stop it — Page type: Tutorial
- [Deployment options](https://docs.helix-db.com/database/helix-db/start-here/run-modes): Compare Cloud, local server, and embedded execution — Page type: Concept
- [Local server](https://docs.helix-db.com/database/helix-db/start-here/local-development/local-server): Start HelixDB locally with memory, a persistent directory, or S3-compatible storage — Page type: Guide
- [Embedded database](https://docs.helix-db.com/database/helix-db/start-here/local-development/embedded-database): Open HelixDB directly inside your process with explicit storage and cache settings — Page type: Guide
- [SDK setup](https://docs.helix-db.com/database/helix-db/start-here/sdk-setup/overview): Choose a HelixDB SDK and connect it to a local or Cloud server — Page type: Guide
- [Rust SDK](https://docs.helix-db.com/database/helix-db/start-here/sdk-setup/rust-project-setup): Build typed HelixDB queries and execute them over HTTP or an embedded engine — Page type: Guide
- [TypeScript SDK](https://docs.helix-db.com/database/helix-db/start-here/sdk-setup/typescript-project-setup): Build typed HelixDB requests for Node.js applications — Page type: Guide
- [Go SDK](https://docs.helix-db.com/database/helix-db/start-here/sdk-setup/go-project-setup): Build and execute HelixDB requests with ordinary Go functions — Page type: Guide
- [Python SDK](https://docs.helix-db.com/database/helix-db/start-here/sdk-setup/python-project-setup): Build HelixDB requests with idiomatic synchronous and asynchronous Python clients — Page type: Guide
- [Roadmap](https://docs.helix-db.com/database/helix-db/start-here/roadmap): What we're building and what's coming next — Page type: Reference
- [Release notes](https://docs.helix-db.com/database/helix-db/start-here/release-notes): New features and changes in HelixDB, Helix Cloud, the SDKs, and the CLI — Page type: Reference

## Core Concepts
- [Data model](https://docs.helix-db.com/database/helix-db/core-concepts/data-model): Understand how HelixDB represents entities, relationships, properties, and indexes — Page type: Concept
- [Build and run a query](https://docs.helix-db.com/database/helix-db/core-concepts/overview): Build a small write query operation by operation, then read its request and response — Page type: Tutorial

## Query Guides
- [Writing data](https://docs.helix-db.com/database/helix-db/query-guides/writing-data): Create, update, connect, and remove entities in one typed write batch — Page type: Guide
- [Reading data](https://docs.helix-db.com/database/helix-db/query-guides/reading-data): Start a traversal from IDs, labels, properties, or previous query results — Page type: Guide
- [Traverse relationships](https://docs.helix-db.com/database/helix-db/query-guides/traversals): Follow edges, retain row-local bindings, and control duplicate paths — Page type: Guide
- [Filtering](https://docs.helix-db.com/database/helix-db/query-guides/filtering): Narrow traversal streams with predicates and exact search candidate sets — Page type: Guide
- [Shape query results](https://docs.helix-db.com/database/helix-db/query-guides/projections): Return properties, computed values, aggregates, and correlated binding rows — Page type: Guide
- [Bind typed query parameters](https://docs.helix-db.com/database/helix-db/query-guides/parameters): Keep the operation tree stable while request values change — Page type: Guide
- [Branch, repeat, and condition queries](https://docs.helix-db.com/database/helix-db/query-guides/advanced): Compose sub-traversals and gate named entries without leaving one transaction — Page type: Guide
- [Query HelixDB with Cypher](https://docs.helix-db.com/database/helix-db/query-guides/cypher): Run Cypher statements beside native queries, and see which parts of openCypher HelixDB supports — Page type: Guide
- [Secondary indexes](https://docs.helix-db.com/database/helix-db/query-guides/secondary-indexes): Accelerate equality, uniqueness, and ordered property lookups — Page type: Guide
- [Vector indexes](https://docs.helix-db.com/database/helix-db/query-guides/vector-indexes): Create vector indexes and run nearest-neighbor search — Page type: Guide
- [Text indexes](https://docs.helix-db.com/database/helix-db/query-guides/text-indexes): Create BM25 indexes and run ranked full-text search — Page type: Guide
- [Prefiltered search](https://docs.helix-db.com/database/helix-db/query-guides/prefiltering): Rank only the nodes or edges a traversal reaches with vector or BM25 search — Page type: Guide
- [Search consistency](https://docs.helix-db.com/database/helix-db/query-guides/search-consistency): Choose whether vector and text searches include unpublished index work, and handle index backpressure — Page type: Guide
- [HelixDB HTTP API and OpenAPI specification](https://docs.helix-db.com/database/helix-db/query-guides/http-api): Call the HelixDB v2 query endpoint and discover its machine-readable OpenAPI 3.1 contract — Page type: Reference
- [Query error reference](https://docs.helix-db.com/database/helix-db/query-guides/error-handling): Branch on stable error codes, apply retry rules, and look up every HelixDB query error — Page type: Reference
- [Troubleshoot HelixDB](https://docs.helix-db.com/database/helix-db/query-guides/troubleshooting): Diagnose query, index, vector, embedded, and local runtime failures — Page type: Troubleshooting

## Helix Cloud — Start Here
- [Get started with Helix Cloud](https://docs.helix-db.com/database/helix-cloud/start-here/using-the-cloud): Sign in, create a workspace and choose its plan, provision a database, and test the connection — Page type: Tutorial
- [Connect to Helix Cloud](https://docs.helix-db.com/database/helix-cloud/start-here/working-with-enterprise): Connect an SDK or HTTP client to a Helix Cloud database and control request routing — Page type: Guide
- [Architecture](https://docs.helix-db.com/database/helix-cloud/start-here/architecture): How the Helix Cloud gateway, writer, readers, caches, and object storage serve reads and writes — Page type: Concept

## Connect and automate
- [Helix Cloud MCP](https://docs.helix-db.com/database/helix-cloud/connect/mcp): Connect users and agents to the unified Helix Cloud MCP endpoint — Page type: Reference

## Operate
- [Security](https://docs.helix-db.com/database/helix-cloud/operate/security): Authenticate requests, handle API keys, and review encryption and enterprise security features — Page type: Reference
- [Multi-tenancy](https://docs.helix-db.com/database/helix-cloud/operate/multi-tenancy): Isolate tenants with storage-level tenant databases, row-level scoping, and tenant-partitioned search indexes — Page type: Guide
- [Guarantees](https://docs.helix-db.com/database/helix-cloud/operate/guarantees): Atomicity, isolation, durability, index activation, and read-after-write behavior — Page type: Reference
- [Limits](https://docs.helix-db.com/database/helix-cloud/operate/limits): Understand Helix Cloud request rate limits and database constraints — Page type: Reference
- [Tradeoffs](https://docs.helix-db.com/database/helix-cloud/operate/tradeoffs): What the Helix Cloud architecture is optimized for, and where another system may fit better — Page type: Concept
- [Helix Cloud gateway errors](https://docs.helix-db.com/database/helix-cloud/operate/error-handling): Use stable Helix Cloud error codes, HTTP statuses, and SDK error metadata — Page type: Reference

## Helix Foundry — Start Here
- [What is Helix Foundry?](https://docs.helix-db.com/foundry/start-here/introduction): Helix Foundry connects your company's data, drafts an ontology across it, and loads it into a Helix database you can explore — Page type: Concept
- [Helix Foundry quickstart](https://docs.helix-db.com/foundry/start-here/quickstart): Sign in, create a workspace's first ontology from a connected source and your documents, load it into a Helix database, ask it a question and explore it — Page type: Tutorial
- [Workspaces and navigation](https://docs.helix-db.com/foundry/start-here/workspaces-and-navigation): Sign in to Helix Foundry, choose or create a workspace, and find your way with the sidebar, the section panels, search and themes — Page type: Guide

## Data
- [Connect and sync data](https://docs.helix-db.com/foundry/data/connect-data): Find your way around Helix Foundry's Connectors section, add a source, test its credential, keep its tables synced and read what each table holds — Page type: Guide
- [Upload and organise documents](https://docs.helix-db.com/foundry/data/documents): Upload Markdown, text, PDF, CSV, JSON, Parquet and other files to a Helix Foundry workspace, keep them in document sets, see how ontologies read each format, and which ontologies read each one — Page type: Guide
- [Connectors](https://docs.helix-db.com/foundry/data/connectors): What each Helix Foundry source needs, the permissions to give it, the tables it syncs and its limits — Page type: Reference
- [API sources](https://docs.helix-db.com/foundry/data/api-sources): Send pieces of data to Helix Foundry from your app or agent, over HTTP or the Helix MCP, with send-only tokens, and choose how ontologies read them — Page type: Guide

## Ontologies
- [Create an ontology](https://docs.helix-db.com/foundry/ontologies/create-an-ontology): Create a Helix Foundry ontology step by step on an existing Helix database or a new one, with its first draft, and read its overview — Page type: Guide
- [Generate and version an ontology](https://docs.helix-db.com/foundry/ontologies/generate-and-version): Ask Helix Foundry's agent to draft an ontology from your synced tables, API sources and document sets, review each version, edit it, and choose the current one — Page type: Guide
- [Load data into a Helix database](https://docs.helix-db.com/foundry/ontologies/load-data): Write an ontology's current version, your synced tables and your documents into its Helix database, and manage its loads — Page type: Guide

## Explore
- [Explore the graph](https://docs.helix-db.com/foundry/explore/explorer): Read what a Helix Foundry load wrote as a graph: search, expand, inspect, pick a load and compare two — Page type: Guide
- [Records and entities](https://docs.helix-db.com/foundry/explore/records-and-entities): Read a Helix Foundry load as tables by type, open a record's links and sources, and see everything about one entity — Page type: Guide

## Ask
- [Ask questions of your data](https://docs.helix-db.com/foundry/ask/ask-questions): Ask a Helix Foundry ontology's load questions in plain language, follow each step, and open the records, rows and quotes its answers cite — Page type: Guide

## Agents
- [Use Foundry from your agent](https://docs.helix-db.com/foundry/agents/helix-mcp): Connect Claude Code, Codex or another MCP client to the Helix MCP to read and ask Helix Foundry ontologies, and to set them up with a confirmation for every change — Page type: Guide

## Workspace
- [Members and roles](https://docs.helix-db.com/foundry/workspace/members-and-roles): See who is in a Helix Foundry workspace, invite people, and what owners, admins and members can do — Page type: Guide
- [Plans and billing](https://docs.helix-db.com/foundry/workspace/plans-and-billing): Compare Helix Foundry Free, Pro and Max, which differ in how often connectors sync, upgrade a workspace, switch tiers, cancel, resume and manage payment — Page type: Guide
- [AI models](https://docs.helix-db.com/foundry/workspace/ai-models): Choose where a Helix Foundry workspace's drafts, document reads and questions run: the default, or your own Anthropic API key on Pro or Max — Page type: Guide
- [Usage and spending caps](https://docs.helix-db.com/foundry/workspace/usage): See what a Helix Foundry workspace has spent on AI this month, on loads, API sources and questions, against each monthly cap — Page type: Guide

## Reference
- [Helix Foundry limits](https://docs.helix-db.com/foundry/reference/limits): Every Helix Foundry limit in one place: syncs, API sources, documents, generations, loads, questions, spending, the Helix MCP and reads — Page type: Reference
- [Troubleshooting Helix Foundry](https://docs.helix-db.com/foundry/reference/troubleshooting): What Helix Foundry's sign-in, connection, sync, API source, document, generation, database, load, Ask, AI model and Helix MCP messages mean, and what to do — Page type: Troubleshooting

## Using the helix CLI
- [Getting started with HelixDB CLI](https://docs.helix-db.com/cli/getting-started): Install the CLI, run locally, or link a WorkOS-authenticated Cloud database — Page type: Tutorial
- [Local development](https://docs.helix-db.com/cli/workflows/local): Run a local instance and iterate on dynamic JSON queries — Page type: Guide
- [Helix Cloud CLI workflow](https://docs.helix-db.com/cli/workflows/helix_cloud): Authenticate, link, query, and manage Cloud resources — Page type: Guide
- [CLI configuration](https://docs.helix-db.com/cli/configuration): Project linkage and WorkOS session files — Page type: Reference
- [CLI troubleshooting](https://docs.helix-db.com/cli/troubleshooting): Recover local and WorkOS-authenticated Cloud CLI operations — Page type: Troubleshooting

## CLI Command Reference
- [CLI command reference](https://docs.helix-db.com/cli/command-reference): Every Helix CLI command, grouped by what it manages — Page type: Reference
- [helix add](https://docs.helix-db.com/cli/command-reference/add): Add a local instance or a Helix Cloud database link to an existing project — Page type: Reference
- [helix auth](https://docs.helix-db.com/cli/command-reference/auth): Log in to Helix Cloud, check the session, or log out — Page type: Reference
- [helix api](https://docs.helix-db.com/cli/command-reference/api): Call a Helix Cloud API endpoint with your CLI login session — Page type: Reference
- [helix chef](https://docs.helix-db.com/cli/command-reference/chef): Bootstrap a first HelixDB app with a coding agent — Page type: Reference
- [helix cluster](https://docs.helix-db.com/cli/command-reference/cluster): List and inspect Helix Cloud clusters and their active indexes — Page type: Reference
- [helix cypher](https://docs.helix-db.com/cli/command-reference/cypher): Execute or explain one Cypher statement against a local instance — Page type: Reference
- [helix database](https://docs.helix-db.com/cli/command-reference/database): Discover and manage Helix Cloud databases and application keys — Page type: Reference
- [helix delete](https://docs.helix-db.com/cli/command-reference/delete): Remove an instance from helix.toml and clean up its local state — Page type: Reference
- [helix doctor](https://docs.helix-db.com/cli/command-reference/doctor): Check an instance's setup: runtime, storage, disk cache, memory, and index use — Page type: Reference
- [helix explorer](https://docs.helix-db.com/cli/command-reference/explorer): Browse a running local instance in the graph Explorer — Page type: Reference
- [helix feedback](https://docs.helix-db.com/cli/command-reference/feedback): Open a pre-filled feedback issue for the Helix team — Page type: Reference
- [helix init](https://docs.helix-db.com/cli/command-reference/init): Create a local project or a WorkOS-authenticated Cloud link — Page type: Reference
- [helix logs](https://docs.helix-db.com/cli/command-reference/logs): View local logs or recent Cloud query errors — Page type: Reference
- [helix metrics](https://docs.helix-db.com/cli/command-reference/metrics): Configure CLI telemetry and usage metrics collection — Page type: Reference
- [helix project](https://docs.helix-db.com/cli/command-reference/project): Discover, manage, and link Helix Cloud projects — Page type: Reference
- [helix prune](https://docs.helix-db.com/cli/command-reference/prune): Remove Helix-owned local containers, volumes, and instance state — Page type: Reference
- [helix query](https://docs.helix-db.com/cli/command-reference/query): Execute a direct Helix v3 query against a local instance or a Cloud database — Page type: Reference
- [helix restart](https://docs.helix-db.com/cli/command-reference/restart): Restart a background local instance — Page type: Reference
- [helix skills](https://docs.helix-db.com/cli/command-reference/skills): Install, refresh, and list the Helix agent skills — Page type: Reference
- [helix start](https://docs.helix-db.com/cli/command-reference/start): Start a local instance in the background or foreground — Page type: Reference
- [helix status](https://docs.helix-db.com/cli/command-reference/status): Inspect local runtime or current Cloud database state — Page type: Reference
- [helix stop](https://docs.helix-db.com/cli/command-reference/stop): Stop a background local instance and remove its containers — Page type: Reference
- [helix service-credential](https://docs.helix-db.com/cli/command-reference/service-credential): Manage workspace-owned credentials for headless HTTP API and unified MCP clients — Page type: Reference
- [helix shell](https://docs.helix-db.com/cli/command-reference/shell): Run line-oriented Helix v3 JSON requests — Page type: Reference
- [helix update](https://docs.helix-db.com/cli/command-reference/update): Update the Helix CLI and refresh installed agent skills — Page type: Reference
- [helix workspace](https://docs.helix-db.com/cli/command-reference/workspace): Discover WorkOS workspace memberships — Page type: Reference

## Learning center
- [Learning center](https://docs.helix-db.com/learn/index): Plain-language answers about graph databases, vector search, full-text search, AI agent memory, and modern database architecture. — Page type: Concept

## Graph databases
- [What is a graph database?](https://docs.helix-db.com/learn/graph-databases/what-is-a-graph-database): A graph database stores things as nodes and the connections between them as edges, and answers questions by following those connections. — Page type: Concept
- [What is the difference between a graph database and a relational database?](https://docs.helix-db.com/learn/graph-databases/graph-vs-relational-database): A relational database keeps data in tables and rebuilds connections with joins; a graph database stores connections as edges and follows them. — Page type: Concept
- [What is a knowledge graph?](https://docs.helix-db.com/learn/graph-databases/what-is-a-knowledge-graph): A knowledge graph is a connected collection of facts about things and how they relate, organized by a schema so software can query and cite it. — Page type: Concept
- [What is a property graph?](https://docs.helix-db.com/learn/graph-databases/what-is-a-property-graph): A property graph stores data as labeled nodes and edges with key-value properties on both, so a relationship can carry its own details. — Page type: Concept
- [What is the difference between a property graph and RDF?](https://docs.helix-db.com/learn/graph-databases/property-graph-vs-rdf): A property graph stores nodes and edges that carry their own properties; RDF stores every fact as a three-part triple named by global IDs. — Page type: Concept

## Vector search
- [What is vector search?](https://docs.helix-db.com/learn/vector-search/what-is-vector-search): Vector search finds results by meaning instead of exact words, by comparing embeddings: lists of numbers that capture what content is about. — Page type: Concept
- [What are vector embeddings?](https://docs.helix-db.com/learn/vector-search/what-are-vector-embeddings): A vector embedding is a list of numbers, produced by a machine learning model, that captures what a piece of content means. — Page type: Concept
- [What is a vector database?](https://docs.helix-db.com/learn/vector-search/what-is-a-vector-database): A vector database stores embeddings, lists of numbers that capture what content means, and quickly finds the ones most similar to a query. — Page type: Concept
- [What is HNSW?](https://docs.helix-db.com/learn/vector-search/what-is-hnsw): HNSW is a vector search index that links each vector to its nearest neighbors in layers, so a search can hop quickly to similar items. — Page type: Concept
- [What is filtered vector search?](https://docs.helix-db.com/learn/vector-search/filtered-vector-search): Filtered vector search finds the most similar items among only those that pass a rule, such as a tenant, a date range, or a permission check. — Page type: Concept
- [What is the difference between cosine, Euclidean, and Manhattan distance?](https://docs.helix-db.com/learn/vector-search/vector-distance-metrics): Cosine distance compares direction, Euclidean measures the straight-line gap, and Manhattan adds up the per-dimension gaps between two embeddings. — Page type: Concept

## Full-text search
- [What is full-text search?](https://docs.helix-db.com/learn/full-text-search/what-is-full-text-search): Full-text search finds documents by the words inside them and lists the best matches first, using an inverted index and a relevance score such as BM25. — Page type: Concept
- [What is BM25?](https://docs.helix-db.com/learn/full-text-search/what-is-bm25): BM25 is a scoring formula that ranks documents for a keyword search by how rare each word is, how often it appears, and how long the document is. — Page type: Concept
- [What is hybrid search?](https://docs.helix-db.com/learn/full-text-search/hybrid-search): Hybrid search runs a keyword search and a vector search for the same query, then merges the results so it finds both exact terms and similar meaning. — Page type: Concept

## AI memory and RAG
- [What is retrieval-augmented generation (RAG)?](https://docs.helix-db.com/learn/ai-memory/what-is-rag): RAG has an AI model answer from documents looked up at question time, so answers can use private, current data and cite their sources. — Page type: Concept
- [What is GraphRAG?](https://docs.helix-db.com/learn/ai-memory/what-is-graphrag): GraphRAG finds context for an AI model by following links between facts in a graph, not only by matching text that is similar to the question. — Page type: Concept
- [What is AI agent memory?](https://docs.helix-db.com/learn/ai-memory/what-is-ai-agent-memory): AI agent memory lets an AI assistant store, update, and recall what it learns across sessions, outside the model's context window. — Page type: Concept
- [How do you build long-term memory for AI agents?](https://docs.helix-db.com/learn/ai-memory/long-term-memory-for-ai-agents): Build agent long-term memory from versioned, user-scoped facts: catch duplicates and forget on write, then search and expand on read. — Page type: Concept

## Database architecture
- [Why build a database on object storage?](https://docs.helix-db.com/learn/database-architecture/object-storage-databases): A database on object storage keeps its data in a durable object store and uses server memory and disks as cache, so storage and compute scale separately. — Page type: Concept
- [Do you need separate graph, vector, and text databases?](https://docs.helix-db.com/learn/database-architecture/one-database-for-graph-vector-and-text): Often not. One database that stores relationships and indexes the same records for vector and keyword search avoids sync pipelines and stale copies. — Page type: Concept

## Content
- [HelixDB Agent Content](https://www.helix-db.com/content): Technical guides about AI memory, GraphRAG, graph-vector databases, and building production AI systems with HelixDB.
- [Open Source Graph Database License for Commercial SaaS](https://www.helix-db.com/content/compare/open-source-graph-database-license-for-commercial-saas): Which open source graph database license for commercial SaaS lets you embed it? HelixDB, LadybugDB, Neo4j, Memgraph, SurrealDB and FalkorDB compared.
- [How to Benchmark a Graph Database for AI Retrieval Accurately](https://www.helix-db.com/content/guides/how-to-benchmark-a-graph-database-for-ai-retrieval-accurately): Learn how to benchmark a graph database for ai retrieval using real query shapes, cold cache runs, memory tiering, and realistic GraphRAG workloads.
- [Best Graph Database for Agentic Memory: Six Tests Before You Pick](https://www.helix-db.com/content/best-graph-database-for-agentic-memory-six-tests-before-you-pick): Evaluating the best graph database for agentic memory? Run these six tests across Neo4j, Memgraph, FalkorDB, LadybugDB, and HelixDB before choosing.
- [Low-Latency Graph Retrieval for AI Agents: Millisecond Bottlenecks](https://www.helix-db.com/content/guides/low-latency-graph-retrieval-for-ai-agents-millisecond-bottlenecks): Diagnose slow context retrieval in your AI agent stack. Learn how to achieve low-latency graph retrieval for AI agents by fixing round trips and fan-out.
- [Memgraph Alternatives for Agent Memory: When RAM Becomes the Limit](https://www.helix-db.com/content/alternatives/memgraph-alternatives-for-agent-memory-when-ram-becomes-the-limit): Evaluating Memgraph alternatives for agent memory? Compare Neo4j, FalkorDB, LadybugDB, and HelixDB on memory efficiency, indexing, and open source licensing.
- [Graph Database on Object Storage: How Agent Memory Scales](https://www.helix-db.com/content/graph-database-on-object-storage-how-agent-memory-scales): Learn how running a graph database on object storage scales AI agent memory, cuts RAM costs, and handles vector indexes with smart caching tiers.
- [Kuzu Alternatives in 2026: Embedded Graph Databases](https://www.helix-db.com/content/alternatives/kuzu-alternatives-in-2026-embedded-graph-databases): Evaluating the best Kuzu alternatives for AI agents and RAG after the repository archive. Compare LadybugDB, HelixDB, Memgraph, and Neo4j.
- [How to Build a Company Brain Knowledge Graph: Docs and People](https://www.helix-db.com/content/guides/how-to-build-a-company-brain-knowledge-graph-docs-and-people): Build a company brain knowledge graph across Slack, Notion, and Drive. Query docs, people, and decisions with HelixDB graph-vector retrieval.
- [How to Give Claude Persistent Memory With Graph-Vector MCP](https://www.helix-db.com/content/guides/how-to-give-claude-persistent-memory-with-graph-vector-mcp): Learn how to give Claude persistent memory using a graph-vector database and MCP server. Stop relying on flat vector files and model real context.
- [Embedded Graph Database for AI Agents: In-Process Setup](https://www.helix-db.com/content/guides/embedded-graph-database-for-ai-agents-in-process-setup): Build local-first AI memory with an embedded graph database for AI agents. Run HelixDB in TypeScript with in-process vector recall and graph traversal.
- [Pinecone Alternative for Agent Memory: When Relationships Matter](https://www.helix-db.com/content/alternatives/pinecone-alternative-for-agent-memory-when-relationships-matter): Looking for a Pinecone alternative for agent memory? Discover why agents require graph relationships alongside vector search and how to pick the right engine.
- [Self-Hosted Vector Database With Graph Queries: HelixDB in Docker](https://www.helix-db.com/content/guides/self-hosted-vector-database-with-graph-queries-helixdb-in-docker): Run a self hosted vector database with graph queries in Docker using HelixDB. Configure storage, load vectors on graph nodes, and execute scoped queries.
- [Migrate from FalkorDB: Move a GraphRAG Graph to HelixDB](https://www.helix-db.com/content/guides/migrate-from-falkordb-move-a-graphrag-graph-to-helixdb): Learn how to migrate from FalkorDB to HelixDB. Follow this source-first guide to capture schemas, batch export graph data, and rewrite Cypher queries in JSON.
- [Migrate from pgvector: Moving Agent RAG Memory to Graphs](https://www.helix-db.com/content/guides/migrate-from-pgvector-moving-agent-rag-memory-to-graphs): Learn how to migrate from pgvector to HelixDB. Keep embeddings intact, turn foreign keys into graph edges, and run hybrid graph-vector queries in one engine.
- [Re-embedding Agent Memory After You Change Models](https://www.helix-db.com/content/guides/re-embedding-agent-memory-after-you-change-models): Learn how to handle re-embedding agent memory without downtime, maintain graph context, and migrate embedding models step by step across parallel indexes.
- [Neo4j Vector Index Memory: Sizing Agent Memory Accurately](https://www.helix-db.com/content/guides/neo4j-vector-index-memory-sizing-agent-memory-accurately): Calculate Neo4j vector index memory with the Lucene HNSW formula. Size agent memory, explore RAM limits, and see how HelixDB tiers storage.
- [How to Combine BM25 and Vector Search in One Query for RAG](https://www.helix-db.com/content/guides/how-to-combine-bm25-and-vector-search-in-one-query-for-rag): Learn how to combine BM25 and vector search for RAG. Avoid two-index drift, implement reciprocal rank fusion, and run hybrid queries in HelixDB.
- [Kuzu Migration Guide: Moving an Archived Kuzu Graph to HelixDB](https://www.helix-db.com/content/guides/kuzu-migration-guide-moving-an-archived-kuzu-graph-to-helixdb): A step-by-step Kuzu migration guide to export your schema, Parquet files, and indexes, then load your graph into HelixDB for agent memory and GraphRAG.
- [Deduplicate Entities in an Agent Memory Knowledge Graph](https://www.helix-db.com/content/guides/deduplicate-entities-in-an-agent-memory-knowledge-graph): Learn how to deduplicate entities in an agent memory knowledge graph using blocking, scoped vectors, multi-signal scoring, and atomic merges in HelixDB.
- [Multi-Tenant Agent Memory: How to Isolate per Tenant](https://www.helix-db.com/content/guides/multi-tenant-agent-memory-how-to-isolate-per-tenant): Learn how to isolate multi-tenant agent memory in one graph-vector database using tenant-partitioned indexes, graph pre-filters, and clean boundary logic.
- [How to Build People Search With a Knowledge Graph](https://www.helix-db.com/content/guides/how-to-build-people-search-with-a-knowledge-graph): Build a people search knowledge graph with embeddings and BM25 in HelixDB. Learn how to prefilter vector search by graph edges to stop lookalike misses.
- [How to Query Agent Memory by Time Range Without a Full Scan](https://www.helix-db.com/content/guides/how-to-query-agent-memory-by-time-range-without-a-full-scan): Query agent memory by time range without a full scan: index the timestamp, traverse from the user, and rank only that window with prefiltered vector search.
- [Shared Memory for Multi-Agent Systems: One Graph to Query](https://www.helix-db.com/content/guides/shared-memory-for-multi-agent-systems-one-graph-to-query): Build shared memory for multi-agent systems using HelixDB. Store agent provenance, supersede outdated facts, and prefilter vector search over a single graph.
- [HelixDB Alternatives: Neo4j, Memgraph, FalkorDB, LadybugDB](https://www.helix-db.com/content/alternatives/helixdb-alternatives-neo4j-memgraph-falkordb-ladybugdb): Weighing HelixDB alternatives for agent memory? See where Neo4j, Memgraph, FalkorDB and LadybugDB each win, and why storage decides the choice.
- [Why Does Hybrid Search Return Fewer Results Than You Asked For?](https://www.helix-db.com/content/why-does-hybrid-search-return-fewer-results-than-you-asked-for): Hybrid search returning fewer than k results is either post-filtering eating your top-k slots or a scoped query hitting its real candidate count.
- [How Do I Let Claude Query My Database Directly with MCP?](https://www.helix-db.com/content/guides/how-do-i-let-claude-query-my-database-directly-with-mcp): Connect Claude to HelixDB Cloud over MCP: one endpoint, no database key, a tool set that differs for agents, and a write that can only be committed once.
- [How to Build a Knowledge Graph From Meeting Notes](https://www.helix-db.com/content/guides/how-to-build-a-knowledge-graph-from-meeting-notes): Learn how to build a knowledge graph from meeting notes. Extract typed entities, resolve speakers, and query decisions without losing context in HelixDB.
- [Moving Off Memgraph: Migrating Agent Memory to HelixDB](https://www.helix-db.com/content/guides/moving-off-memgraph-migrating-agent-memory-to-helixdb): Moving off Memgraph for agent memory? Audit your Cypher schema, export it cleanly, and rewrite retrieval so graph traversal, vector search and BM25 run in one query.
- [Semantic Search Over Internal Documents Is Not Enough](https://www.helix-db.com/content/semantic-search-over-internal-documents-is-not-enough): Semantic search over internal documents misses answers that live in a relationship rather than a chunk. Here is what a graph-vector engine does instead.
- [Open Source Graph Database Written in Rust: How HelixDB Is Built](https://www.helix-db.com/content/open-source-graph-database-written-in-rust-how-helixdb-is-built): HelixDB is an open source graph database written in Rust that runs graph traversal, vector search and BM25 full-text in one engine. Here is how it is built.
- [How to Give AI Agents Persistent Memory in One Database](https://www.helix-db.com/content/guides/how-to-give-ai-agents-persistent-memory-in-one-database): Give AI agents memory that survives restarts: model episodes as timestamped nodes and edges, then scope semantic recall to one user with a graph traversal.
- [How to Build a GraphRAG Pipeline: From Documents to Scoped Retrieval](https://www.helix-db.com/content/guides/how-to-build-a-graphrag-pipeline-from-documents-to-scoped-retrieval): Learn how to build a GraphRAG pipeline to solve multi-hop Q&A. This guide covers entity extraction, graph modeling, and scoped retrieval using HelixDB.
- [HelixDB vs LadybugDB: Picking a Graph DB After Kuzu](https://www.helix-db.com/content/compare/helixdb-vs-ladybugdb-picking-a-graph-db-after-kuzu): Kuzu is archived. LadybugDB is columnar and analytical, in-process or in the browser. HelixDB is OLTP agent memory with pre-filtered vector and keyword search.
- [How to Migrate from Neo4j to HelixDB: A Migration Guide](https://www.helix-db.com/content/guides/how-to-migrate-from-neo4j-to-helixdb-a-migration-guide): Migrate from Neo4j to HelixDB: map the graph, export a checksummed snapshot, load it with replay-safe batches, translate your Cypher, and verify before cutover.
- [Pre-Filtering Vector Search on Graph Edges: How to Scope ANN to Relationships](https://www.helix-db.com/content/guides/pre-filtering-vector-search-on-graph-edges-how-to-scope-ann-to-relationships): Learn how to scope vector search on graph edges for precise RAG. Move beyond flat ANN scans by filtering embeddings within specific relationships and subgraphs.
- [HelixDB vs FalkorDB: Choosing a Graph Database for GraphRAG](https://www.helix-db.com/content/compare/helixdb-vs-falkordb-choosing-a-graph-database-for-graphrag): HelixDB vs FalkorDB for GraphRAG: in-memory speed against object-storage scale. Compare pre-filtering, high availability, licensing and what each one costs.
- [Vector Database vs Graph Database: What AI Memory Needs](https://www.helix-db.com/content/vector-database-vs-graph-database-what-ai-memory-needs): An architectural comparison of vector vs graph databases for AI memory. Learn why HelixDB replaces the duct-taped RAG stack with a single Rust engine.
- [HelixDB vs Memgraph: Which Graph Database for AI Memory?](https://www.helix-db.com/content/compare/helixdb-vs-memgraph-which-graph-database-for-ai-memory): HelixDB vs Memgraph: in-memory graph analytics against object-storage-backed agent memory. Which one actually scales, and what does each one cost to run?
- [HelixDB vs Neo4j: Graph and Vector Search in One Engine](https://www.helix-db.com/content/compare/helixdb-vs-neo4j-graph-and-vector-search-in-one-engine): Compare HelixDB vs Neo4j for GraphRAG and agent memory. Learn why a unified Rust engine beats a bolted-on vector approach for high-performance AI applications.
- [AI Agent Memory Architecture: Why Vector Search Is Not Enough](https://www.helix-db.com/content/ai-agent-memory-architecture-why-vector-search-is-not-enough): Learn why modern AI agent memory architecture requires knowledge graphs. Compare GraphRAG vs. vector search and see how HelixDB unifies both in one Rust engine.