How do I install Llmstxt Doc Search?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Llmstxt Doc Search need an API key?

No required environment variable is listed on this record.

What transport does Llmstxt Doc Search use?

Llmstxt Doc Search runs locally over stdio.

When was Llmstxt Doc Search last checked?

Last checked 2026-10-28. BM25 search over llms.txt doc indexes (Strands, Kiro, AWS); sources addable at runtime.

Llmstxt Doc Search MCP server

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Add to Cursor Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Local command

npx -y @praveenc/[email protected]

Claude Code has no install link for a local command. Copy the command below and run it in a terminal.

shClaude Code

1claude mcp add io.github.praveenc-llmstxt-doc-search -- npx -y @praveenc/llmstxt-doc-search@1.0.0

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.praveenc-llmstxt-doc-search": {4      "command": "npx",5      "args": [6        "-y",7        "@praveenc/[email protected]"8      ]9    }10  }11}

claude_desktop_config.json

Local · npmPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Version: 1.0.0
Last checked

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

llmstxt-doc-search

Live, ranked search across any number of llms.txt documentation sites - Strands, Kiro, the AWS guides, and whatever you add at runtime.

llmstxt-doc-search is a Model Context Protocol (MCP) server that turns the llms.txt index a documentation site publishes into a fast, ranked search tool your agent can call. It indexes titles at startup, ranks queries with BM25, and fetches the full document only when you open a result - so you get current docs with almost no local storage. Built on the search engine from @praveenc/mcp-docs-server, generalized to a runtime registry of sources.

It implements the MCP 2026-07-28 specification over stdio and still works with clients on the 2025 protocol, which open with an initialize handshake. Requires Node.js 20 or later.

Why

An llms.txt file is a curated index of a doc site's pages, published for tools like this one to consume. They can be large - AWS Bedrock's lists roughly a thousand documents - so downloading everything is wasteful and goes stale fast.

This server takes a leaner approach:

Title-only index, built lazily. On first search of a source, only the page titles are indexed. That is fast to build and tiny to hold in memory.
Ranked with BM25. Queries are scored with BM25 plus Porter stemming, bigrams, and markdown-aware weighting (headers, code, and links count for more). Technical terms like mcp, json, and stdio are preserved rather than stemmed.
Content on demand. The full markdown or HTML of a result is fetched only when you call fetch_doc.

The result is a good fit for broad, fast-moving reference material - the opposite tradeoff to snapshotting docs into a local vault.

Installation

Quick start (recommended)

Add the server to your MCP client configuration (Claude Desktop, Kiro, and others). It is downloaded and run on demand via npx - no manual build:

{
  "mcpServers": {
    "llmstxt-doc-search": {
      "command": "npx",
      "args": ["-y", "@praveenc/llmstxt-doc-search"]
    }
  }
}

Global install

npm install -g @praveenc/llmstxt-doc-search

Then point your MCP client at the installed binary:

{
  "mcpServers": {
    "llmstxt-doc-search": {
      "command": "llmstxt-doc-search"
    }
  }
}

Quick start

Once the server is connected, the typical flow is three calls:

docs_home() - orient yourself: see the registered sources and how to search and fetch.
search_docs("prompt caching", "aws-bedrock-userguide") - rank matching docs. Omit the source to search everything.
fetch_doc(url) - read the full content of a result you like.

Add your own source at any time and it is indexed immediately and persisted for future runs:

add_doc_source("langgraph", "https://langchain-ai.github.io/langgraph/llms.txt")

Tools

Tool	Purpose
`docs_home()`	Orientation: registered sources plus how to search and fetch. Call this first.
`list_doc_sources()`	List sources with their `llms.txt` URL and index status, including the last index error for a failing source.
`search_docs(query, source?, k?)`	BM25 search. Omit `source` to search all, or scope to one. Returns ranked `{source, url, title, score, snippet}`, where `score` (0-1) is comparable across sources. `k` defaults to 5 (max 50).
`fetch_doc(url)`	Fetch the full content of a result URL. The URL must be under the `llms.txt` directory of a registered source, or listed in the `llms.txt` of a source that has been indexed (by a search, add, or refresh).
`add_doc_source(name, llms_txt_url)`	Register and index a new `llms.txt` source at runtime. Persisted. Rejected if that `llms.txt` is already registered or contains no links.
`remove_doc_source(name)`	Remove a registered source.
`refresh_doc_source(name)`	Re-index a source to pick up new or changed docs. A source whose `llms.txt` fails to index is skipped for 5 minutes; this retries it immediately.

docs_home, list_doc_sources, search_docs, and fetch_doc are annotated read-only, so a client can approve them without prompting. add_doc_source, remove_doc_source, and refresh_doc_source change the persisted registry, and remove_doc_source is annotated destructive. The tool list is fixed, so it is advertised as cacheable for one hour.

Default sources

Seeded into the registry on first run:

strands, kiro, aws-bedrock-userguide, aws-agentic-ai-lens, aws-bedrock-agentcore-devguide, mcp.

The registry is persisted at ~/.config/llmstxt-doc-search/sources.json (override with LLMSTXT_REGISTRY_PATH). Anything you add, remove, or refresh at runtime is saved there.

Configuration

All configuration is via environment variables; none are required.

Variable	Default	Meaning
`LLMSTXT_REGISTRY_PATH`	`~/.config/llmstxt-doc-search/sources.json`	Where the source registry is persisted.
`LLMSTXT_SNIPPET_HYDRATE_MAX`	`5`	How many top hits to fetch when building result snippets.
`LLMSTXT_PAGE_CACHE_MAX`	`50`	Max fetched pages kept in memory per source (LRU); least-recently-used pages are evicted past this. `0` disables the cap.
`LLMSTXT_LOG_LEVEL`	`info`	Log verbosity: `debug`, `info`, `warn`, or `error`. Logs go to stderr only.

Testing with MCP Inspector

npx @modelcontextprotocol/inspector npx -y @praveenc/llmstxt-doc-search

The Inspector can connect in either protocol era; see Protocol eras.

Development

Clone the repository for local work (Node.js 20 or later):

git clone https://github.com/praveenc/llmstxt-doc-search.git
cd llmstxt-doc-search
npm install

Commands

npm run dev         # run from source with tsx (no build)
npm test            # offline unit and protocol tests
npm run typecheck   # type-check without emitting
npm run build       # compile to dist/
npm run inspect:dev # MCP Inspector against the source

Local MCP client config (development)

Point your client at a source checkout instead of the published package:

{
  "mcpServers": {
    "llmstxt-doc-search": {
      "command": "npx",
      "args": ["tsx", "/ABS/PATH/llmstxt-doc-search/src/index.ts"]
    }
  }
}

Or, after npm run build, at the compiled entry point:

{
  "mcpServers": {
    "llmstxt-doc-search": {
      "command": "node",
      "args": ["/ABS/PATH/llmstxt-doc-search/dist/index.js"]
    }
  }
}

Architecture

src/
├── index.ts              # Tool registration and the stdio entry point (serves 2026-07-28 and 2025-era clients)
├── config.ts             # Defaults and environment configuration
├── tools/
│   └── docs.ts           # search_docs, fetch_doc, and source management
└── utils/
    ├── doc-fetcher.ts    # HTTP fetching, redirect handling, HTML parsing
    ├── indexer.ts        # BM25 search index
    ├── registry.ts       # Persisted source registry
    ├── store.ts          # In-memory document store
    ├── text-processor.ts # Tokenization and snippet helpers
    ├── url-validator.ts   # SSRF guard and URL validation
    ├── stopwords.ts      # Stop-word list
    └── logger.ts         # Logging utilities

Search algorithm

Ranking uses BM25 (Best Matching 25) with several enhancements:

Porter stemming matches word variants (for example, running and run).
Bigrams capture phrase matches (for example, prompt caching).
Weighted scoring boosts title matches (3-8x), headers (4x), code blocks (2x), and link text (2x).
Domain-term preservation keeps technical terms like mcp, json, and stdio unstemmed so they match exactly.

Security

This server fetches user-supplied URLs at runtime, so its SSRF surface is guarded in depth:

Scoped fetches. fetch_doc only retrieves URLs that a registered source's llms.txt lists exactly, or that sit under that source's origin and path prefix (matched on a path boundary rather than a raw string prefix). There is no arbitrary fetch.
Scheme allow-list. Non-http(s) schemes are rejected.
Range-based address blocking. Private and reserved destinations are blocked using IP range classification (ipaddr.js), covering decimal, octal, and hex IPv4, IPv4-mapped IPv6, loopback, link-local, unique-local, carrier-grade NAT, and other reserved ranges - not just a hostname regex.
Connection-time validation. The resolved IP is checked at connection time via a custom DNS lookup, closing DNS-rebinding, and every redirect hop is re-validated.
Bounded responses. Response bodies are capped at 10 MB to limit memory and regular-expression (ReDoS) exposure.

Runtime dependencies report zero known vulnerabilities.

License

Contributing

Contributions are welcome. If you find a bug or have an idea:

Open an issue describing the problem or proposal.
For code changes, fork the repo and create a feature branch.
Keep changes focused, add or update tests, and make sure npm test, npm run typecheck, and npm run build all pass.
Open a pull request against main with a clear description of what changed and why.

Commit messages follow the Conventional Commits style.

Support

Questions and ideas: open a GitHub issue.
Bugs: please include your MCP client, the tool call you made, and any relevant logs (set LLMSTXT_LOG_LEVEL=debug for more detail).
Security issues: open an issue marked as security-sensitive, or contact the maintainer directly rather than posting exploit details publicly.

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Llmstxt Doc Search?

Does Llmstxt Doc Search need an API key?

What transport does Llmstxt Doc Search use?

When was Llmstxt Doc Search last checked?

Documentation

llmstxt-doc-search

Why

Installation

Quick start (recommended)

Global install

Quick start

Tools

Default sources

Configuration

Testing with MCP Inspector

Development

Commands

Local MCP client config (development)

Architecture

Search algorithm

Security

License

Contributing

Support