annolab.ai valid
Anno Lab API (V1)
For agents: Anno Lab API (V1) reference and Python SDK for the AnnoLab data annotation platform: projects, directories, source files and setup.
annotation platform apidata labelingpython sdkml training dataprojects and source files
- Authority
- 46 reach 0 · trust 10 · quality 21 · freshness 15
- Tier
- listed
- llms.txt
- https://docs.annolab.ai/llms.txt
- llms-full.txt
- https://docs.annolab.ai/llms-full.txt
- Sections
- 1
- Links
- 22
- Size
- 3814 bytes
- Registered
- 2020-12-03
- Country
- — Publisher location unknown; CDN address excluded
- Country evidence
- No published address evidence collected yet
- Categories
- APIs and SDKs · AI and machine learning
- For agents
- Interface: a documented API or declared MCP endpoint an agent can call
- Inferred actions
- Read documentation Call an API About these labels
- Audience
- developers · agents can: read docs, call api · en
- First seen
- 2026-10-25T11:28:14.762Z
- Last checked
- 2026-10-25T11:28:17.158Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-25T11:28:14.774Z. Cached copy · Source on annolab.ai
# Anno Lab API (V1)
## Anno Lab API (V1)
- [Setup](https://docs.annolab.ai/master.md): Learn how to get your API key and how to send requests to the platform.
- [AnnoLab SDK](https://docs.annolab.ai/master/annolab-sdk.md): Python SDK to interact with AnnoLab
- [Projects](https://docs.annolab.ai/projects-directories-and-sources/projects.md): Projects are the highest level abstraction in the Annotation Lab platform. They contain directories, source files, schemas, and annotation layers. They are also the scope at which work can be shared.
- [Directories](https://docs.annolab.ai/projects-directories-and-sources/directories.md): Directories are containers for Source Files that can be used to help organize the contents of a project
- [Source Files](https://docs.annolab.ai/projects-directories-and-sources/source-files.md): Source files are files that contain things you want to annotate or run models on. Currently we support PDF and .txt file formats
- [Upload Sources](https://docs.annolab.ai/projects-directories-and-sources/upload-sources.md): Upload PDF source files using a three-step process: initialize an upload, PUT the file to a signed URL, then confirm creation and start processing.
- [Annotation Types](https://docs.annolab.ai/schemas-ontologies/annotation-types.md): Annotation types are the valid annotation labels that can be applied to source material.
- [Model Inferences](https://docs.annolab.ai/schemas-ontologies/model-inferences.md): Inferences are how you request model predictions of annotations on your source files
- [Annotations](https://docs.annolab.ai/annotations-and-relations/annotations.md): Annotations one of the fundamental building blocks of extracted data. They say that a portion of a source has some special meaning
- [Canonical Tags](https://docs.annolab.ai/annotations-and-relations/canonical-tags.md): Unique entities described by a set of annotations
- [Land Instruments](https://docs.annolab.ai/annotations-and-relations/land-instruments.md): Land instruments are returned by the Search a Land Abstract endpoint
- [Conveyances](https://docs.annolab.ai/annotations-and-relations/conveyances.md): Conveyances describe tract-level interests contained within land instruments
- [Instruments](https://docs.annolab.ai/annotations-and-relations/instruments.md): Instruments are a special format produced by Export Instruments and Search Instruments
- [Relations](https://docs.annolab.ai/annotations-and-relations/relations.md)
- [Annotation Layers](https://docs.annolab.ai/annotations-and-relations/annotation-layers.md): Annotation layers are containers for annotations and can be used to "version" annotations and experiment outputs.
- [Export Instruments](https://docs.annolab.ai/exports/export-instruments.md): Export instrument level data so that you can consume the data in your own internal applications
- [Export Project](https://docs.annolab.ai/exports/export-project.md): Export projects so that you can train your own ML models
- [Search Instr
…Related sites
Similar publisher descriptions and documentation. Similarity does not imply affiliation or equivalent capabilities.
| Domain | Title | Category | Country | Authority | llms.txt | llms-full.txt | Save |
|---|---|---|---|---|---|---|---|
| labellerr.com | Labellerr (labellerr.com) | documentation AI and machine learning Data and analytics | US | 53 | ✓ | ||
| labelstud.io | API Reference | Label Studio | interface APIs and SDKs AI and machine learning +1 | — | 54 | ✓ | ✓ | |
| v7labs.com | V7 Darwin Resources & Documentation Documentation | documentation AI and machine learning Documentation and reference | — | 59 | ✓ | ||
| dwaste.live | Annotate-Lab | documentation | — | 46 | ✓ | ✓ | |
| superannotate.com | SuperAnnotate | Streamline AI Data Workflows | documentation AI and machine learning Data and analytics | US | 59 | ✓ | ||
| basic.ai | BasicAI | interface AI and machine learning Industry and manufacturing +2 | US | 50 | ✓ | ||
| projectdiscovery.io | ProjectDiscovery llms.txt | interface Cybersecurity Developer tools | US | 49 | ✓ | ||
| animl.camera | Animl docs | documentation AI and machine learning Science and research | — | 46 | ✓ | ✓ |
Machine-readable: GET /v1/resolve?q=annolab.ai · GET /v1/domain/annolab.ai · this page as Accept: application/json or text/markdown · MCP lookup_domain
Automatically discovered from public files. Inclusion does not imply endorsement or publisher participation.
Own or manage this website?
If you own or manage annolab.ai, you can update its listing and review file health, discovery activity and score history.
Manage this listing — optional
What verification unlocks
See how your site is discovered—and control what agents see.
- See your website in the map
Review your indexed topics, nearby publishers sharing headings, measured listing exposure and map snapshots in a private report for your website.
- Control what agents see
Edit your listing description, tags, public contact details and additional llms.txt paths. Publish your terms for automated access, attribution and pricing.
- Make your profile eligible for search
A valid, listed, unblocked, verified profile can appear in our publisher sitemap and become eligible for search-engine visibility. Search engines decide what to index and rank.
- Appear in our llms-full.txt
Eligible verified publishers are listed by name, with their file links and summaries, in the service overview agents can read.
Free. No account registration, backlink or payment required. Public discovery remains available without verification.
Let your coding agent verify it
If your coding agent is authorized to manage this website, paste these instructions into it.
Claim my listing on Agent Web Map for annolab.ai:
1. POST https://agentwebmap.com/v1/sites/annolab.ai/claims and keep claim_id and claim_secret private.
2. Publish the verification line "AgentWebMap verification: <token>" (token from step 1) in https://annolab.ai/llms.txt, or use the DNS, meta-tag or well-known method the response describes. This only verifies the listing; your website and domain remain yours.
3. POST https://agentwebmap.com/v1/sites/annolab.ai/verify with {"claim_id": "...", "claim_secret": "..."}.
4. Save the api_key from the answer; it manages the listing (PATCH https://agentwebmap.com/v1/sites/annolab.ai).
MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verifyCorrections or removal requests: contact the directory.