docsearch-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DOCSEARCH_DIR | No | Path to the folder of .md/.txt/.rst documents to search. Defaults to a built-in corpus of Python standard-library docstrings when not set. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_docsA | Search the indexed documents with BM25. Returns the top k chunks with their source, relevance score and text, so answers can cite the source. |
| list_sourcesC | Number of indexed chunks and the list of source documents. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one searches content by relevance, the other enumerates indexed sources. There is no realistic way to confuse a BM25 search with listing sources.
Both names follow the same verb_noun snake_case pattern (search_docs, list_sources). The convention is predictable and readable.
Two tools is thin for a search server; useful capabilities like fetching a full document or filtering search by source are absent. Still, the count is not absurd for a narrowly scoped read-only index.
Core retrieval and source enumeration are covered, but there is no way to retrieve a whole document, filter searches by source, or manage the index. Agents hitting a chunk boundary or needing document-level context will dead-end.