Codeseeker

Graph-powered code intelligence with semantic search and knowledge graph for AI assistants

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "codeseeker": {
      "command": "npx",
      "args": [
        "-y",
        "work"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

CodeSeeker

Four-layer hybrid search and knowledge graph for AI coding assistants.
BM25 + vector embeddings + RAPTOR directory summaries + graph expansion — fused into a single MCP tool that gives Claude, Copilot, and Cursor a real understanding of your codebase.

Works with Claude Code, GitHub Copilot (VS Code 1.99+), Cursor, Windsurf, and Claude Desktop.
One command to index; the Claude Code plugin keeps it in sync from there.

The Problem

AI assistants are powerful editors, but they navigate code like a tourist:

Grep finds text — not meaning. "find authentication logic" returns every file containing the word "auth"
File reads are isolated — Claude sees a file but not its dependencies, callers, or the patterns your team established
No memory of your project — every session starts from scratch

CodeSeeker fixes this. It indexes your codebase once and gives AI assistants a queryable knowledge graph they can use on every turn.

How It Works

A 4-stage pipeline runs on every query:

Code

Query: "find JWT refresh token logic"
        │
        ▼  Stage 1 — Hybrid retrieval
   ┌─────────────────────────────────────────────────────┐
   │ BM25 (exact symbols, camelCase tokenized)           │
   │   +                                                 │
   │ Vector search (384-dim Xenova embeddings)           │
   │   ↓                                                 │
   │ Reciprocal Rank Fusion: score = Σ 1/(60 + rank_i)  │
   │ Top-30 results, including RAPTOR directory nodes    │
   └─────────────────────────────────────────────────────┘
        │
        ▼  Stage 2 — RAPTOR cascade (conditional)
   ┌─────────────────────────────────────────────────────┐
   │ IF best directory-summary score ≥ 0.5:              │
   │   → narrow results to that directory automatically  │
   │ ELSE: all 30 results pass through unchanged         │
   │ Effect: "what does auth/ do?" scopes to auth/       │
   │         "jwt.ts decode function" bypasses this      │
   └─────────────────────────────────────────────────────┘
        │
        ▼  Stage 3 — Scoring and deduplication
   ┌─────────────────────────────────────────────────────┐
   │ Dedup: keep highest-score chunk per file            │
   │ Source files:  +0.10  (definition sites matter)     │
   │ Test files:    −0.15  (prevent test dominance)      │
   │ Symbol boost:  +0.20  (query token in filename)     │
   │ Multi-chunk:   up to +0.30  (file has many hits)    │
   └─────────────────────────────────────────────────────┘
        │
        ▼  Stage 4 — Graph expansion
   ┌─────────────────────────────────────────────────────┐
   │ Top-10 results → follow IMPORTS/CALLS/EXTENDS edges │
   │ Structural neighbors scored at source × 0.7        │
   │ Avg graph connectivity: 20.8 edges/node             │
   └─────────────────────────────────────────────────────┘
        │
        ▼
   auth/jwt.ts (0.94), auth/refresh.ts (0.89), ...

The knowledge graph is built from AST-parsed imports at index time. It's what powers the graph action, dead-code detection, and graph expansion in every search.

What Makes It Different

Approach	Strengths	Limitations
Grep / ripgrep	Fast, universal	No semantic understanding
Vector search only	Finds similar code	Misses structural relationships
Serena	Precise LSP symbol navigation, 30+ languages	No semantic search, no cross-file reasoning
Codanna	Fast symbol lookup, good call graphs	Semantic search needs JSDoc — undocumented code gets no embeddings; no BM25, no RAPTOR, Windows experimental
CodeSeeker	BM25 + embedding fusion + RAPTOR + graph + coding standards + multi-language AST	Requires initial indexing (30s–5min)

What LSP tools can't do:

"Find code that handles errors like this" → semantic pattern search
"What validation approach does this project use?" → auto-detected coding standards
"Show me everything related to authentication" → graph traversal across indirect dependencies

What vector-only search misses:

Direct import/export chains
Class inheritance hierarchies
Which files actually depend on which

Installation

Recommended: npx (no install needed)

The standard way to configure any MCP server — no global install required:

config.json

{
  "mcpServers": {
    "codeseeker": {
      "command": "npx",
      "args": ["-y", "codeseeker", "serve", "--mcp"]
    }
  }
}

Add this to your MCP config file (see below for per-client locations) and restart your editor.

npm global install

Terminal

npm install -g codeseeker
codeseeker install --vscode      # or --cursor, --windsurf

🔌 Claude Code Plugin

For Claude Code CLI users — adds auto-sync hooks and slash commands:

bash

/plugin install codeseeker@github:jghiringhelli/codeseeker#plugin

Slash commands: /codeseeker:init, /codeseeker:reindex

☁️ Devcontainers / GitHub Codespaces

config.json

{
  "name": "My Project",
  "image": "mcr.microsoft.com/devcontainers/javascript-node:18",
  "postCreateCommand": "npm install -g codeseeker && codeseeker install --vscode"
}

✅ Verify

Ask your AI assistant: "What CodeSeeker tools do you have?"

You should see a single tool named codeseeker. That is intentional: one tool with an action routing key keeps per-request token overhead low (ADR-002). The actions are search, sym, graph, analyze and index.

Advanced Installation Options

📋 MCP Configuration by client

The MCP config JSON is the same for all clients — only the file location differs:

Client	Config file
VS Code (Claude Code / Copilot)	`.vscode/mcp.json` in your project, or `~/.vscode/mcp.json` globally
Cursor	`.cursor/mcp.json` in your project
Claude Desktop	`~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or `%APPDATA%\Claude\claude_desktop_config.json` (Windows)
Windsurf	`.windsurf/mcp.json` in your project

config.json

{
  "mcpServers": {
    "codeseeker": {
      "command": "npx",
      "args": ["-y", "codeseeker", "serve", "--mcp"]
    }
  }
}

🖥️ CLI Standalone Usage (without AI assistant)

Terminal

npm install -g codeseeker
cd your-project
codeseeker init
codeseeker -c "how does authentication work in this project?"

What You Get

CodeSeeker exposes one MCP tool, codeseeker. You pick behaviour with action and fill only the matching nested parameter group:

codeseeker({ action, project, search?|sym?|graph?|analyze?|index? })

Always pass project (the absolute project root) — an MCP server cannot detect your working directory.

action	Parameters	What It Does
`search`	`search:{q}`	Hybrid search: BM25 + vector embeddings fused with RRF, then graph expansion; RAPTOR directory summaries surface for abstract queries
`search`	`search:{q, type:"vector"}`	Pure embedding cosine-similarity search
`search`	`search:{q, type:"fts"}`	Pure BM25 text search with CamelCase tokenisation
`search`	`search:{q, full:true}`	Include a code snippet with each result (default: summaries only)
`search`	`search:{q, exists:true}`	Quick yes/no — returns `{found, count, top_file}`
`sym`	`sym:{name}`	Look up a class/function by name and show its graph neighbours
`graph`	`graph:{seed, depth, rel, dir}`	Traverse the knowledge graph from a file (imports, calls, extends)
`graph`	`graph:{q}`	Same, but find the seed files semantically first
`analyze`	`analyze:{kind:"standards"}`	Your project's detected patterns (validation, error handling)
`analyze`	`analyze:{kind:"duplicates"}`	Find duplicate/similar code blocks
`analyze`	`analyze:{kind:"dead_code"}`	Detect unused exports, orphaned files, coupling issues
`index`	`index:{op:"init", path}`	Build the index for a project (required once — see below)
`index`	`index:{op:"sync", changes}`	Update the index for specific files
`index`	`index:{op:"exclude", paths}`	Exclude/include paths from the index
`index`	`index:{op:"status"}`	List indexed projects with file/chunk counts
`index`	`index:{op:"parsers"}`	List/install Tree-sitter parsers

You don't invoke these manually—Claude uses them automatically when searching code or analyzing relationships.

How Indexing Works

A project must be indexed once before search works. CodeSeeker does not index on first query — if the project is unknown it returns an error telling you to initialise it. This is deliberate: silently indexing a large repository inside a tool call would block the assistant for minutes with no way to cancel.

Code

User: "Find the authentication logic"
        │
        ▼
┌──────────────────────────────────────────────┐
│ Claude calls codeseeker({action:"search"})   │
│         │                                    │
│         ▼                                    │
│ Project indexed? ──No──► error: run          │
│         │                index op:"init"     │
│        Yes                                   │
│         ▼                                    │
│ Return ranked results                        │
└──────────────────────────────────────────────┘

Index once, either way:

codeseeker({ action: "index", index: { op: "init", path: "/abs/path/to/project" } })

bash

codeseeker init          # or, from the CLI

Read the full README →View source on GitHub →

Related MCP Servers

View all in Developer Tools View all alternatives

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Codeseeker

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "codeseeker": { "command": "npx", "args": ["-y", "codeseeker"] } }

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Technical Specs & Signals

CategoryDeveloper Tools

39Quality signal: Fair · 39/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity3/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Codeseeker

Graph-powered code intelligence with semantic search and knowledge graph for AI assistants

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "codeseeker": {
      "command": "npx",
      "args": [
        "-y",
        "work"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

CodeSeeker

Works with Claude Code, GitHub Copilot (VS Code 1.99+), Cursor, Windsurf, and Claude Desktop.
One command to index; the Claude Code plugin keeps it in sync from there.

The Problem

AI assistants are powerful editors, but they navigate code like a tourist:

Grep finds text — not meaning. "find authentication logic" returns every file containing the word "auth"
File reads are isolated — Claude sees a file but not its dependencies, callers, or the patterns your team established
No memory of your project — every session starts from scratch

CodeSeeker fixes this. It indexes your codebase once and gives AI assistants a queryable knowledge graph they can use on every turn.

How It Works

A 4-stage pipeline runs on every query:

Code

Query: "find JWT refresh token logic"
        │
        ▼  Stage 1 — Hybrid retrieval
   ┌─────────────────────────────────────────────────────┐
   │ BM25 (exact symbols, camelCase tokenized)           │
   │   +                                                 │
   │ Vector search (384-dim Xenova embeddings)           │
   │   ↓                                                 │
   │ Reciprocal Rank Fusion: score = Σ 1/(60 + rank_i)  │
   │ Top-30 results, including RAPTOR directory nodes    │
   └─────────────────────────────────────────────────────┘
        │
        ▼  Stage 2 — RAPTOR cascade (conditional)
   ┌─────────────────────────────────────────────────────┐
   │ IF best directory-summary score ≥ 0.5:              │
   │   → narrow results to that directory automatically  │
   │ ELSE: all 30 results pass through unchanged         │
   │ Effect: "what does auth/ do?" scopes to auth/       │
   │         "jwt.ts decode function" bypasses this      │
   └─────────────────────────────────────────────────────┘
        │
        ▼  Stage 3 — Scoring and deduplication
   ┌─────────────────────────────────────────────────────┐
   │ Dedup: keep highest-score chunk per file            │
   │ Source files:  +0.10  (definition sites matter)     │
   │ Test files:    −0.15  (prevent test dominance)      │
   │ Symbol boost:  +0.20  (query token in filename)     │
   │ Multi-chunk:   up to +0.30  (file has many hits)    │
   └─────────────────────────────────────────────────────┘
        │
        ▼  Stage 4 — Graph expansion
   ┌─────────────────────────────────────────────────────┐
   │ Top-10 results → follow IMPORTS/CALLS/EXTENDS edges │
   │ Structural neighbors scored at source × 0.7        │
   │ Avg graph connectivity: 20.8 edges/node             │
   └─────────────────────────────────────────────────────┘
        │
        ▼
   auth/jwt.ts (0.94), auth/refresh.ts (0.89), ...

The knowledge graph is built from AST-parsed imports at index time. It's what powers the graph action, dead-code detection, and graph expansion in every search.

What Makes It Different

Approach	Strengths	Limitations
Grep / ripgrep	Fast, universal	No semantic understanding
Vector search only	Finds similar code	Misses structural relationships
Serena	Precise LSP symbol navigation, 30+ languages	No semantic search, no cross-file reasoning
Codanna	Fast symbol lookup, good call graphs	Semantic search needs JSDoc — undocumented code gets no embeddings; no BM25, no RAPTOR, Windows experimental
CodeSeeker	BM25 + embedding fusion + RAPTOR + graph + coding standards + multi-language AST	Requires initial indexing (30s–5min)

What LSP tools can't do:

"Find code that handles errors like this" → semantic pattern search
"What validation approach does this project use?" → auto-detected coding standards
"Show me everything related to authentication" → graph traversal across indirect dependencies

What vector-only search misses:

Direct import/export chains
Class inheritance hierarchies
Which files actually depend on which

Installation

Recommended: npx (no install needed)

The standard way to configure any MCP server — no global install required:

config.json

{
  "mcpServers": {
    "codeseeker": {
      "command": "npx",
      "args": ["-y", "codeseeker", "serve", "--mcp"]
    }
  }
}

Add this to your MCP config file (see below for per-client locations) and restart your editor.

npm global install

Terminal

npm install -g codeseeker
codeseeker install --vscode      # or --cursor, --windsurf

🔌 Claude Code Plugin

For Claude Code CLI users — adds auto-sync hooks and slash commands:

bash

/plugin install codeseeker@github:jghiringhelli/codeseeker#plugin

Slash commands: /codeseeker:init, /codeseeker:reindex

☁️ Devcontainers / GitHub Codespaces

config.json

{
  "name": "My Project",
  "image": "mcr.microsoft.com/devcontainers/javascript-node:18",
  "postCreateCommand": "npm install -g codeseeker && codeseeker install --vscode"
}

✅ Verify

Ask your AI assistant: "What CodeSeeker tools do you have?"

Advanced Installation Options

📋 MCP Configuration by client

The MCP config JSON is the same for all clients — only the file location differs:

Client	Config file
VS Code (Claude Code / Copilot)	`.vscode/mcp.json` in your project, or `~/.vscode/mcp.json` globally
Cursor	`.cursor/mcp.json` in your project
Claude Desktop	`~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or `%APPDATA%\Claude\claude_desktop_config.json` (Windows)
Windsurf	`.windsurf/mcp.json` in your project

config.json

{
  "mcpServers": {
    "codeseeker": {
      "command": "npx",
      "args": ["-y", "codeseeker", "serve", "--mcp"]
    }
  }
}

🖥️ CLI Standalone Usage (without AI assistant)

Terminal

npm install -g codeseeker
cd your-project
codeseeker init
codeseeker -c "how does authentication work in this project?"

What You Get

CodeSeeker exposes one MCP tool, codeseeker. You pick behaviour with action and fill only the matching nested parameter group:

codeseeker({ action, project, search?|sym?|graph?|analyze?|index? })

Always pass project (the absolute project root) — an MCP server cannot detect your working directory.

action	Parameters	What It Does
`search`	`search:{q}`	Hybrid search: BM25 + vector embeddings fused with RRF, then graph expansion; RAPTOR directory summaries surface for abstract queries
`search`	`search:{q, type:"vector"}`	Pure embedding cosine-similarity search
`search`	`search:{q, type:"fts"}`	Pure BM25 text search with CamelCase tokenisation
`search`	`search:{q, full:true}`	Include a code snippet with each result (default: summaries only)
`search`	`search:{q, exists:true}`	Quick yes/no — returns `{found, count, top_file}`
`sym`	`sym:{name}`	Look up a class/function by name and show its graph neighbours
`graph`	`graph:{seed, depth, rel, dir}`	Traverse the knowledge graph from a file (imports, calls, extends)
`graph`	`graph:{q}`	Same, but find the seed files semantically first
`analyze`	`analyze:{kind:"standards"}`	Your project's detected patterns (validation, error handling)
`analyze`	`analyze:{kind:"duplicates"}`	Find duplicate/similar code blocks
`analyze`	`analyze:{kind:"dead_code"}`	Detect unused exports, orphaned files, coupling issues
`index`	`index:{op:"init", path}`	Build the index for a project (required once — see below)
`index`	`index:{op:"sync", changes}`	Update the index for specific files
`index`	`index:{op:"exclude", paths}`	Exclude/include paths from the index
`index`	`index:{op:"status"}`	List indexed projects with file/chunk counts
`index`	`index:{op:"parsers"}`	List/install Tree-sitter parsers

You don't invoke these manually—Claude uses them automatically when searching code or analyzing relationships.

How Indexing Works

Code

User: "Find the authentication logic"
        │
        ▼
┌──────────────────────────────────────────────┐
│ Claude calls codeseeker({action:"search"})   │
│         │                                    │
│         ▼                                    │
│ Project indexed? ──No──► error: run          │
│         │                index op:"init"     │
│        Yes                                   │
│         ▼                                    │
│ Return ranked results                        │
└──────────────────────────────────────────────┘

Index once, either way:

codeseeker({ action: "index", index: { op: "init", path: "/abs/path/to/project" } })

bash

codeseeker init          # or, from the CLI

Read the full README →View source on GitHub →

Related MCP Servers

View all in Developer Tools View all alternatives

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Codeseeker

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "codeseeker": { "command": "npx", "args": ["-y", "codeseeker"] } }

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Technical Specs & Signals

CategoryDeveloper Tools

39Quality signal: Fair · 39/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity3/15

Community engagement0/10

★ Spotlight Slot

Feature Your MCP Server

Get maximum visibility for your server across our directory, search results, and detail pages.

Spotlight Your Server

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 💻 Developer Tools →Best MCP servers for Developers →Alternatives to Codeseeker →Install in Claude Desktop Install in Cursor Install in VS Code