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lemuelflores

mcp-semantic-search

by lemuelflores

πŸ” mcp-semantic-search

Ask your specs a question instead of grepping them.

An MCP server & CLI that gives AI agents local semantic search over markdown docs β€” running 100% on your machine by default.


Why use this?

Traditional grep misses ideas that don't match exact keywords.

mcp-semantic-search understands intent across your local specs, RFCs, and internal docs.

$ mcp-semantic-search search "how do we stop repeated failed logins"

--- Result 1  [0.688]  content ---
file: auth.md
section: Sessions > Credential attempts

After five consecutive bad passwords the account enters a 15-minute
cooling-off period. The counter resets on any successful sign-in.

--- Result 2  [0.541]  content ---
file: gateway.md
section: Rate limits > Edge throttling

A single IP address is capped at 20 requests per minute against
/session endpoints. Anything beyond that receives a 429 before it
ever reaches the application.

Notice: Neither chunk contains the words "failed" or "login" β€” grep -ri "failed login" returns nothing at all. Semantic search finds both halves of the answer: the account lockout in the auth spec, and the network throttle that backs it up in a different file with entirely different vocabulary.


Related MCP server: search-docs

Key Features

  • 🧱 Structure-Aware Chunking β€” Splits markdown on heading boundaries (H1–H4) without breaking code blocks or tables.

  • πŸ”’ Local & Private β€” Runs via LanceDB & Ollama. Zero docs leave your machine.

  • πŸ—ΊοΈ Document Maps β€” Generates outline (toc) chunks so agents can scan doc structures before reading details.

  • ⚑ Zero-Overhead Indexing β€” File hashes ensure re-indexing only happens when files actually change.

  • 🎯 Targeted Filtering β€” Filter search by filename, heading, or chunk type (content, code, table, toc).


Quick Start

1. Requirements & Build

Requires Node.js 22+ and Ollama (or a Gemini API key).

# Pull default model
ollama pull qwen3-embedding:0.6b

# Clone & Build
git clone <repo-url> mcp-semantic-search
cd mcp-semantic-search
npm install && npm run build

2. Run locally (CLI)

Inside the target repository you want to index:

cd ~/projects/my-app
echo '.mcp-search/' >> .gitignore

/path/to/mcp-semantic-search index
/path/to/mcp-semantic-search search "how are expired sessions cleaned up"

Setup as an MCP Server

Add to your project's .mcp.json:

{
  "mcpServers": {
    "specs": {
      "type": "stdio",
      "command": "node",
      "args": ["/absolute/path/to/mcp-semantic-search/dist/index.js"]
    }
  }
}

MCP Tools Exposed

  • index β€” Indexes your markdown specs directory (set reindex: true to force rebuild).

  • search β€” Queries indexed documents (query, file, section, chunk_type, limit, min_score).

  • status β€” Checks index health, chunk counts, and staleness.

Agent Prompting Tip (CLAUDE.md): Add this to your project's CLAUDE.md: "Search specs using the specs MCP server. Run index first if status shows the index as missing or stale."


Configuration

Set environment variables in your shell or directly inside .mcp.json under the "env" block.

Global Settings

Variable

Default

Purpose

EMBEDDING_BACKEND

ollama

Vector provider: ollama or gemini

SPECS_DIR

<project>/specs

Absolute path to markdown specs

DB_PATH

<project>/.mcp-search

Where LanceDB index is stored

MIN_SCORE

0.44

Default similarity threshold

Ollama Backend (Default)

Variable

Default

Purpose

OLLAMA_BASE_URL

http://localhost:11434

Endpoint for Ollama daemon

OLLAMA_EMBEDDING_MODEL

qwen3-embedding:0.6b

Embedding model to use

Gemini Backend (Cloud Option)

Variable

Default

Purpose

GEMINI_API_KEY

(Required)

Required when EMBEDDING_BACKEND=gemini

GEMINI_EMBEDDING_MODEL

gemini-embedding-001

Embedding model to use

GEMINI_EMBEDDING_DIMENSIONS

768

Vector width (128–3072)

Note: Changing backends automatically triggers a clean index rebuild on the next run.

Example .mcp.json with Custom Config

{
  "mcpServers": {
    "specs": {
      "type": "stdio",
      "command": "node",
      "args": ["/absolute/path/to/mcp-semantic-search/dist/index.js"],
      "env": {
        "SPECS_DIR": "/absolute/path/to/my-app/docs",
        "EMBEDDING_BACKEND": "gemini",
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

CLI Options

mcp-semantic-search search <query> [options]

Flag

Description

Default

--file <str>

Filter by matching filename

β€”

--section <str>

Filter by matching section heading

β€”

--chunk-type <type>

content | code | table | toc

All

--limit <n>

Max results to return

5

--min-score <f>

Similarity floor (0.0–1.0)

0.44

--json

Output raw JSON instead of plain text

false


License

MIT

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