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CodeSeek

A local code-intelligence CLI that gives coding assistants semantic search and call-graph queries.

View on GitHub ↗ Quick start ↓
Source repo
CodeBendKit/codeseek
Stars
★ 759
Last updated
3mo ago
License
MIT
Primary language
Rust
FA score
48/100 · Major gaps

At a glance

How it runs
CLIMCP serverAgent plugin / skill
Works with
Universal · cross-platformCodex · Claude Code
Cost
Free software; you pay for model usage
Setup effort
Low · running in minutes
You'll need
npm or Homebrew for packaged installationan OpenAI-compatible embedding API tokenShell / CLINetwork accessLocal filesystemMCP Server
Typical use
A Claude Code user exploring a large Rust or TypeScript repository wants to locate relevant functions from a natural-language question.
Not a fit if
  • Windows or Linux arm64 users: npm binaries cover only macOS and Linux x64
  • Teams needing cross-project queries, shared indexes, or access controls
Source review
48/100 · Major gaps

What does this agent do, and when should you use it?

CodeSeek is a Rust-powered code-intelligence CLI designed for Claude Code and Codex CLI workflows. It parses Rust, Python, JavaScript, TypeScript, Go, C/C++, and Java with Tree-sitter, extracting functions, classes, and methods for a call graph. Its local project index combines LanceDB vectors, a Tantivy BM25 index, and a serialized PetCodeGraph under ~/.codeseek/<project_hash>/. Search can combine dense, sparse, and graph retrieval through RRF, then optionally rerank results with Qwen3-Reranker; if embedding or reranking is unavailable, it falls back to graph-based name search. It has no daemon or HTTP server: commands run as standalone processes, while MCP mode uses stdio JSON-RPC.

With codeseek init, CodeSeek reads source files, parses supported languages through Tree-sitter ASTs, and extracts functions, classes, and methods. It batches 20 texts per embedding API request, caches embeddings in SQLite, stores vectors in LanceDB, builds a Tantivy BM25 index, serializes a PetCodeGraph call graph, and uses MD5 hashes to reprocess only changed files. With codeseek search <query>, it obtains a query vector and runs LanceDB ANN dense search, Tantivy BM25 sparse search, and PetCodeGraph graph search; Reciprocal Rank Fusion combines candidates and Qwen3-Reranker-4B can rerank them. The callers, callees, and callgraph commands return upstream and downstream symbol relationships, while codeseek install writes MCP configuration for Claude Code and Codex.

  1. A Claude Code user exploring a large Rust or TypeScript repository wants to locate relevant functions from a natural-language question.
  2. An engineer maintaining a Python, Java, or Go service needs to identify a function’s callers and downstream dependencies before changing it.
  3. A developer working in a mixed-language repository wants one local index of functions, classes, methods, and call relationships.
  4. A Codex CLI user wants MCP-accessible code search and call-graph tools for the repository currently being worked on.
  5. A developer who regularly commits code wants post-commit and post-merge hooks to refresh the local index automatically.

How do you install or deploy this agent?

Install with npm: npm install -g codeseek, then run codeseek for the first-run interactive setup. The wizard configures an embedding API token, model, and base URL; the documented example uses an OpenAI-compatible provider and Qwen/Qwen3-Embedding-4B. Homebrew installation is: brew tap CodeBendKit/codeseek [email protected]:CodeBendKit/codeseek.git && brew install codeseek. For a source build, install protoc, then run git clone https://github.com/CodeBendKit/codeseek.git, cd codeseek, and ./build.sh --release.

How do you use this agent?

From the project directory, run codeseek init to build the index. Run codeseek search main --limit 10 for symbol search, or codeseek search 'how the code embedding work' for a natural-language query. Use codeseek callers <symbol>, codeseek callees <symbol>, or codeseek callgraph <symbol> for call relationships; query commands support --json. Run codeseek install to write MCP configuration to ~/.claude.json or ./.mcp.json and ~/.codex/config.toml. Run codeseek install-hooks to install post-commit and post-merge indexing hooks.

What are this agent's strengths and limitations?

Pros
  • Combines Tree-sitter structural extraction, PetCodeGraph call graphs, LanceDB vector search, and Tantivy BM25 in one local CLI.
  • Its retrieval path can fuse dense, sparse, and graph results with RRF, then apply optional Qwen3-Reranker-4B cross-encoder reranking.
  • MD5-based incremental updates, SQLite embedding caching, and Git hooks reduce the need for full reindexing after every change.
  • It documents native MCP installation for both Claude Code and Codex CLI, including five code-intelligence tools.
Limitations
  • Semantic retrieval requires an embedding API token, model, and base URL, so it depends on network access and has undocumented API-cost implications.
  • The documented Qwen3-Reranker-4B stage adds roughly 1–2 seconds to search-time ranking.
  • Packaged npm binaries are documented only for macOS arm64/x64 and Linux x64; support for other platforms is not established.
  • The documented language scope is limited to seven languages, and the available material does not establish cross-project querying, access controls, or shared team indexes.

How does this agent compare with similar options?

Key facts side by side with the most closely related agents.

Agent Source review Form / cost Stars Updated Language Full support on
CodeSeek This agent 48 · Major gaps CLIFree + model costs ★ 759 3mo ago Rust Codex · Claude Code
GraphMind Code Graph 64 · Some gaps Desktop appFreemium ★ 217 22d ago Rust Claude Code · Claude.ai
Empryo 50 · Major gaps CLIFree + model costs ★ 1.6k 21d ago TypeScript OpenAI API · Claude API
CodeGraph 44 · Major gaps CLIFree + model costs ★ 912 1mo ago Rust Claude Code · OpenAI API · Claude API

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
48/ 100 5-point scale 2.4 / 5
Trust 10/29
Reliability 6/14
Adaptability 12/18
Convention 10/18
Effectiveness 7/13
Verifiability 3/8
Why each dimension lost points
Trust10 / 29 · 1.7/5

Evidence shows: CLI requires API token for embedding and reranking, but config stored in user directory, no hardcoded credentials found. Installation downloads binary via npm script, but no verification of download source. MCP integration modifies config files, but uninstall command provided. No malicious behavior found, but least privilege, user confirmation, data flow transparency, sensitive data handling, dependency security, external effects, rollback, and source attribution are only partially satisfied due to lack of detailed documentation and verification.

Reliability6 / 14 · 2.1/5

Evidence shows: README and code structure consistent, command descriptions clear. But relies on external APIs (embedding, reranking) and binary download, no offline mode or degradation strategy. Failure messages not detailed in documentation.

Adaptability12 / 18 · 3.3/5

Evidence shows: Targeted at AI coding agents, supports multiple languages and platforms, multiple installation methods. Capability boundaries described in README, but trigger precision (e.g., search query accuracy) not detailed. Environment fit good, but no specific IDE or editor integration mentioned.

Convention10 / 18 · 2.8/5

Evidence shows: README structure clear, installation notes detailed, command naming stable, examples provided. But known limitations not explicitly listed, version changelog missing, maintenance responsibility unclear. License is MIT, but copyright year 2026 may be inaccurate.

Effectiveness7 / 13 · 2.7/5

Evidence shows: Output supports JSON for machine readability. Provides search and call graph features, has marginal value. But cost-benefit not analyzed, external API dependency may incur costs.

Verifiability3 / 8 · 1.9/5

Evidence shows: README claims consistent with code structure, but no test results or independent verification. Facts and inferences not clearly separated.

Risks and how to mitigate them
  • API token stored in config file, ensure file permissions are secure.
  • Binary download source not verified, supply chain risk.
  • Relies on external APIs, may incur costs and privacy concerns.
  • MCP integration modifies config files, handle with caution.
Evidence confidence: Low Reviewed Aug 09, 2026 Reviewed revision 981bd23800d1
Review evidence README.mdLICENSEpackage.jsonworkflows/release.ymljs/car.jsjs/main.jspython/calculator.py
See the full review method →

Recent releases

Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.

  1. v0.1.31
    Release notes excerpt
    Full Changelog: https://github.com/CodeBendKit/codeseek/compare/v0.1.30...v0.1.31
    View on GitHub ↗
  2. v0.1.30
    Release notes excerpt
    What's Changed * fix(esbuild): lower L2 threshold, add fingerprint, exclude out/ from … by @iohub in https://github.com/CodeBendKit/codeseek/pull/12 * chore(deps): update lance dependency to 8.0.0 by @iohub in https://github.com/CodeBendKit/codeseek/pull/13 Full Changelog: https://github.com/CodeBendKit/codeseek/compare/v0.1.29...v0.1.30
    View on GitHub ↗
  3. v0.1.29
    Release notes excerpt
    What's Changed * feat: add code skeleton and snippet query functionality by @iohub in https://github.com/CodeBendKit/codeseek/pull/11 Full Changelog: https://github.com/CodeBendKit/codeseek/compare/v0.1.28...v0.1.29
    View on GitHub ↗

FAQ

Can it work without embedding or reranking access?
Yes, with reduced search behavior. The documented fallback is PetCodeGraph-based name search when embeddings or the reranker are unavailable.
Where does the index live, and what leaves the machine?
The local index is stored in ~/.codeseek/<project_hash>/, including vector data, BM25 data, the call graph, and file hashes. Text is sent to the configured embedding API in batches during indexing.
How does it integrate with Claude Code and Codex CLI?
codeseek install writes their MCP configuration, and codeseek serve --mcp provides a stdio JSON-RPC MCP server with search, call-graph, and status tools.
Does it require a running service?
No. The documented execution model is standalone processes for commands, with no daemon and no HTTP server.
View on GitHub ↗ Install ↓

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