MCP tools

All tools are read-only and answer with JSON as text. You rarely call them by name: ask your agent in plain language and it picks the tool. The example prompts below show what tends to trigger each one.

search#

Full-text search over tools (called topics) and their sources. It matches names, roles, regions, detection signals (files, dependencies, environment variables), source titles and URLs. Every word must match, as a prefix, so post finds Postgres.

Input	Type	Description
query	string, 1 to 200 characters	Words to search for, such as database, vercel mcp or turbo.json
kind	optional	Only return sources of this kind: llms, full, docs, mcp, skill, rules or guide
limit	optional, 1 to 50	Maximum number of topics, default 10

Each result has the topic (without its sources), the matching sources and a score (lower is better). When the topic itself matched, sources holds all of its sources; when only some sources matched, just those.

Example prompts

• "Which Postgres hosts does contextatlas know?"
• "Find the MCP server for Vercel in contextatlas."
• "This repo has a turbo.json. What does contextatlas have for it?"

Example call and answer (shortened)

{ "query": "neon", "limit": 1 }

{
  "query": "neon",
  "results": [
    {
      "topic": {
        "id": "neon",
        "name": "Neon",
        "role": "Postgres database",
        "signals": [
          { "type": "dependency", "pattern": "@neondatabase/serverless" },
          { "type": "hint", "pattern": "DATABASE_URL pointing to *.neon.tech" }
        ],
        "region": { "id": "cloud", "name": "Cloud providers" }
      },
      "sources": [
        { "kind": "llms", "title": "Neon llms.txt", "url": "https://neon.com/llms.txt" },
        { "kind": "mcp", "title": "Neon MCP server", "url": "https://neon.com/docs/ai/neon-mcp-server" }
      ],
      "score": -4.32
    }
  ]
}

get_topic#

Everything the catalog has on one tool: its role, region, detection signals and all sources, plus llmsTxt, the URL of the topic's own small llms.txt file.

Input	Type	Description
id	string	Topic id as returned by search or list_topics, such as vercel, nextjs or drizzle

Example prompts

• "Get the contextatlas topic for Drizzle and read its llms.txt."
• "What sources does contextatlas list for Cloudflare?"

Example call and answer (shortened)

{ "id": "drizzle" }

{
  "updatedAt": "2026-10-23",
  "topic": {
    "id": "drizzle",
    "name": "Drizzle ORM",
    "role": "ORM",
    "signals": [
      { "type": "file", "pattern": "drizzle.config.ts" },
      { "type": "dependency", "pattern": "drizzle-orm" }
    ],
    "sources": [
      { "kind": "llms", "title": "Drizzle llms.txt", "url": "https://orm.drizzle.team/llms.txt" }
    ],
    "region": { "id": "frameworks", "name": "Frameworks" },
    "llmsTxt": "https://contextatlas.dev/llms/drizzle.txt"
  }
}

An unknown id returns an error result, so the agent knows to search instead:

{ "error": "Unknown topic \"nope\". Use search or list_topics to find ids." }

list_topics#

Every tool in the catalog with its id, name, role and region, without sources. Agents use it to find the candidates for each role, then call get_topic and read their llms.txt sources to choose. The catalog does not rank tools.

Input	Type	Description
region	optional string	Only this region: cloud, frameworks, standards or clis

Example prompts

• "List the hosting options in contextatlas and pick one for a Next.js app."
• "What agent standards does contextatlas cover?"

Example call and answer (shortened)

{ "region": "standards" }

{
  "updatedAt": "2026-10-23",
  "topics": [
    {
      "id": "agent-skills",
      "name": "Agent Skills",
      "role": "Instructions",
      "region": "standards"
    },
    {
      "id": "agents-md",
      "name": "AGENTS.md",
      "role": "Instructions",
      "region": "standards"
    }
  ]
}

Source kinds#

The kind of a source tells the agent what to do with it:

Kind	Meaning	What the agent should do
llms	llms.txt, a machine-readable index of the docs	Fetch first
rules	Prompts and rule files to paste into an agent	Fetch first and follow
guide	How to work with agents on this platform	Read when relevant
docs	Full documentation or reference	Fetch the pages the task needs
full	All docs in one file, often several megabytes	Download and search it, never read it whole
mcp	An MCP server of the vendor	Offer to connect it, ask first
skill	Installable agent skills	Offer to install, ask first