mcp-docs-ask
Local RAG MCP for documentation. Point source at any markdown repository
(local path or git URL).
The server does retrieval only (no answer LLM). ask_docs returns grounded
passages and citations; the MCP host (Cursor / Claude) synthesizes the answer.
Features
ask_docsretrieval with configurable path-based layer filterslist_docsdiscovery for configured docs collections and layer filtersreindexrebuilds the local vector index; for git URL sources it also fetches updates
Requirements
- Python 3.13+
uvgiton PATH (only ifsourceis a git URL)- Git credentials on the machine when
sourceis a private git URL (gh auth login, HTTPS credential helper, or SSH). No tokens in config. - First run downloads the embedding model weights once (sentence-transformers)
Quick start
git clone git@github.com:alyiox/mcp-docs-ask.git
cd mcp-docs-ask
uv sync
mkdir -p ~/.config/mcp-docs-ask
cp config.example.json ~/.config/mcp-docs-ask/config.json
# Prefer a local checkout while developing:
# set docs.<id>.source to your docs repo path
npx -y @modelcontextprotocol/inspector uv run mcp-docs-ask
Configuration
Config path: ~/.config/mcp-docs-ask/config.json
Windows:
%USERPROFILE%\.config\mcp-docs-ask\config.json
{
"docs": {
"product": {
"source": "https://github.com/example/docs.git",
"desc": "Product guides and API reference",
"ref": "main",
"include": ["**/*.md"],
"exclude": ["archive/**"],
"layers": {
"guides": {
"desc": "How-to and onboarding guides",
"include": ["docs/guides/**"]
},
"api": {
"desc": "HTTP API reference",
"include": ["docs/api/**"]
}
},
"embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
},
"team-notes": {
"source": "/path/to/docs",
"desc": "Internal team notes (local path; ref unused)",
"include": ["**/*.md"],
"exclude": ["archive/**"]
}
},
"default": {
"docs": "product",
"embedding_model": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
"top_k": 8,
"chunk_max_chars": 1500
}
}
product is a git URL (ref applies). team-notes is a filesystem path (ref unused).
Optional desc on each docs collection and layer helps agents pick the right target.
embedding_model, top_k, and chunk_max_chars resolve as:
docs.<id>.X → default.X → built-in. Omit per-docs keys to inherit.
Embedding model recommendation
Any Hugging Face id loadable by sentence-transformers works. Pick by language mix:
| Docs / queries | Recommended embedding_model |
|---|---|
| English-only (built-in when omitted) | sentence-transformers/all-MiniLM-L6-v2 |
| Chinese-only | BAAI/bge-small-zh-v1.5 |
| Multilingual (~50 langs) | sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 |
Changing embedding_model requires a reindex (the on-disk index stores the model name).
| Field | Description |
|---|---|
docs.<id>.source | Docs repo root: local path or git URL |
docs.<id>.desc | Short description for discovery (list_docs) |
docs.<id>.ref | Branch / tag / SHA for git URL sources only (default main; ignored for local paths) |
docs.<id>.include | Globs relative to repo root (default **/*.md) |
docs.<id>.exclude | Globs to skip |
docs.<id>.layers.<name>.include | Path globs for that layer (first match wins) |
docs.<id>.layers.<name>.desc | Short layer description for discovery |
docs.<id>.embedding_model | Optional override (see recommendation above) |
docs.<id>.top_k | Optional override for default retrieval count |
docs.<id>.chunk_max_chars | Optional override for max body chars per heading chunk |
default.docs | Default docs collection id |
default.embedding_model | Default sentence-transformers model id |
default.top_k | Default retrieval count |
default.chunk_max_chars | Default max body chars per heading chunk |
Layers partition indexed files by path glob. First match wins. Names are
case-insensitive; all is reserved (cannot be configured as a layer name).
ask_docs layer | Meaning |
|---|---|
all (default) | Every indexed chunk (named layers and paths outside them) |
<named> | Only chunks whose path matched that named layer’s include globs |
Paths that match no named-layer glob are still indexed and only appear under
layer=all. Omit layers (or set "layers": {}) for flat repos — use
layer=all.
Cache layout:
- Repos (git URL):
~/.cache/mcp-docs-ask/repos/<docs-id>/ - Indexes:
~/.cache/mcp-docs-ask/indexes/<docs-id>/
Tools
| Tool | Description |
|---|---|
list_docs | List configured docs collections and their layer filters |
ask_docs | Retrieve grounded passages + citations (layer: all or a named layer) |
reindex | Sync git source (if URL) and rebuild the vector index |
list_docs returns a default block with the same keys as the config default
block (docs, embedding_model, top_k, chunk_max_chars), plus a docs list
where each entry carries its resolved values and a default flag.
layer_filters is all plus named layer ids — see Layers above.
MCP host examples
Cursor
Add to .cursor/mcp.json:
{
"mcpServers": {
"docs-ask": {
"command": "uvx",
"args": ["mcp-docs-ask"]
}
}
}
Claude Code
Add to your Claude Code MCP config:
{
"mcpServers": {
"docs-ask": {
"command": "uvx",
"args": ["mcp-docs-ask"]
}
}
}
Codex
[mcp_servers.docs-ask]
command = "uvx"
args = ["mcp-docs-ask"]
OpenCode
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"docs-ask": {
"type": "local",
"enabled": true,
"command": ["uvx", "mcp-docs-ask"]
}
}
}
GitHub Copilot
{
"inputs": [],
"servers": {
"docs-ask": {
"type": "stdio",
"command": "uvx",
"args": ["mcp-docs-ask"]
}
}
}
Development
uv sync
uv run ruff check src/ tests/
uv run ruff format --check src/ tests/
uv run pyright
uv run pytest
Notes
- Local path:
ask_docsrebuilds the index automatically when file mtimes/sizes change (fingerprint check). You do not needreindexafter editing local docs. - Git URL:
ask_docsnever fetches. Callreindextogit fetchthe configuredrefand rebuild. - Changing
embedding_modelinvalidates the on-disk index (rebuild on next use /reindex).