octocode
Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI
Install / Use
claude mcp add bgauryy -- npx -y github:bgauryy/octocodeIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of octocode
octocode scores 93/100 on our quality scale, 201st of 965 AI & Machine Learning skills we index (top 21%).
Its MCP Server is 35 KB long, well organised into 40 sections with 17 code examples: a thorough specification that gives an agent plenty to work with.
It has 957 GitHub stars, a meaningful sign that others use it.
Maintenance, license and trust
- The repository was last updated yesterday, so octocode is actively maintained.
- Our last check on 2026-10-18 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
octocode compared with similar skills
All 4 of these similar skills score higher than octocode; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| octocode (this skill)by bgauryy | 93 | 957 | 1d ago | MCP Server |
| claude-memby thedotmack | 100 | 113.5k | today | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 109.2k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 90.9k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.9k | today | CLAUDE.md |
Frequently asked questions
- How do I install octocode?
- Run
claude mcp add bgauryy -- npx -y github:bgauryy/octocode. The install tabs above show the steps for each supported agent. - Which AI agents does octocode work with?
- It is written for Claude Code, Claude Desktop and Cursor, as a MCP Server file. Other agents that read the same format can often use it too.
- Is octocode safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is octocode still maintained?
- The repository was last updated yesterday, so octocode is actively maintained.
Skill content
View source on GitHubOctocode: agentic research platform
<div align="center"> <img src="https://github.com/bgauryy/octocode/raw/main/packages/octocode-mcp/assets/logo_white.png" width="400px" alt="Octocode Logo"> </div>Evidence-first code research for AI agents and developers.
Octocode researches your local code and external code alike (GitHub repositories, PRs, npm) with one toolset: ripgrep + AST search, trees, precise reads, and LSP. Use it as a CLI or MCP server, backed by a Rust engine for fast, token-efficient results across single files or mega-repos.
Table of contents
- Quick start
- Why Octocode
- Built for research (benchmarks)
- Tools
- MCP
- CLI
- Configuration
- Authentication methods
- Security
- Language support
- Skills
- Architecture
- Documentation
- Troubleshooting
- Agent workflows
Quick start
Prerequisites: Node.js 20.12+
1. Run the Octocode CLI with npx
npx octocode --help
2. Authenticate with GitHub - optional, but unlocks private repositories and higher API rate limits:
npx octocode auth login
npx octocode status # verify the active token source
3. Choose your interface. Same tools and Rust engine on both. (Clone is on by default in the CLI, opt-in for MCP.)
🖥️ CLI - research straight from your terminal:
npx octocode
🤖 MCP - one-click install:
- <img src="https://cursor.com/deeplink/mcp-install-dark.svg" alt="Install in Cursor">
- <img src="https://img.shields.io/badge/VS_Code-Install_Server-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white" alt="Install in VS Code">
- <img src="https://img.shields.io/badge/VS_Code_Insiders-Install_Server-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white" alt="Install in VS Code Insiders">
- <img src="https://img.shields.io/badge/Windsurf-Install_Server-1a1a1a?style=flat-square&logoColor=white" alt="Install in Windsurf">
- <img src="https://kiro.dev/images/add-to-kiro.svg" alt="Install in Kiro">
- <img src="https://goose-docs.ai/img/extension-install-dark.svg" alt="Install in Goose">
- <img src="https://files.lmstudio.ai/deeplink/mcp-install-light.svg" alt="Install in LM Studio">
Claude Code:
claude mcp add-json octocode --scope user '{"command":"npx","type":"stdio","args":["octocode-mcp@latest"]}'
</details>
Any other client: npx octocode install
Use it as an MCP server
Add to your MCP client config (or use a one-click install above):
{
"octocode": {
"command": "npx",
"type": "stdio",
"args": ["octocode-mcp@latest"]
}
}
Put a GitHub token and options under env (see Configuration).
Use it as an agentic-friendly CLI
Run npx octocode and agents figure out the rest. The bare command prints built-in usage and the full tool catalog, so any coding agent knows how to drive it out of the box, no MCP client or extra wiring required.
npx octocode # self-describing usage for agents
npx octocode tools # list every tool
npx octocode tools localSearchCode --scheme # inspect a tool's schema
Every MCP tool is also a plain command: JSON in, token-efficient YAML out. Local paths route to local tools; owner/repo[/path] routes to GitHub.
npx octocode tools localSearchCode \
--queries '{"path":".","searchText":"authenticate","maxFiles":20}'
results:
- id: localSearchCode-1
data:
files:
- path: src/auth.ts
matches:
- line: 12
value: "export async function authenticate(req: Request) {"
Learn more at octocode.ai.
Why Octocode
Agents code better from evidence than from guesses. Octocode researches two worlds with one flow, your local code and external code on GitHub and npm, and hands back compact, citable context before an agent changes, reviews, or explains code. Code is truth; context is the map.
Most tools do one slice (web search, or grep your repository) and hand back a fixed blob. Octocode covers the whole loop and lets the agent decide what data it needs next:
- Agent-driven, efficient flows. Instead of one-shot dumps, Octocode chains cheap steps into an optimized research flow: broad code search, then fetch only the exact matched lines/region, with smart pagination and out-of-the-box minification so the model never over-fetches. Every result carries next-step hints to the cheapest follow-up.
- Scales to monorepos. Spot a pattern in one repository, follow the PR that introduced it, then trace it across other repositories and your own files, without leaving the chat. Clone any repository and study it locally.
- Smart GitHub flow. Parallel bulk queries across code, PRs, commits, issues, and repositories, all with the same search-broad, read-narrow, trace-semantically discipline.
- Works without GitHub. Clone any repository and point the local tools (search, AST, LSP, content) at it, same evidence-first flow.
- Reads shape, not noise. On-the-fly minify/skeletonize across 70+ languages: a 100 KB file in a few hundred tokens, not walls of boilerplate.
- Fast, self-contained. Search, parsing, navigation, and redaction run in one prebuilt Rust engine: quick on a laptop or a mega-repo, nothing extra to install.
- Safe by default. Every byte to the model is scanned and secrets redacted first (see Security).
What you can do (whenever the next step needs proven context, not a guess):
| Need | Use Octocode to | |------|-----------------| | Codebase questions | Search local or GitHub code, read exact regions, browse trees, and carry file/line anchors into the answer. | | Implementation research | Compare patterns across repositories, npm packages, pull requests, commits, and local files before changing code. | | Semantic navigation | Resolve definitions, references, callers/callees, call hierarchy, hovers, symbols, diagnostics, and type relationships through LSP. | | Structural matching | Run AST-shaped searches with patterns or YAML rules so comments and strings do not become false positives. | | Large-file context | Minify, skeletonize, or paginate code so agents spend tokens on relevant structure instead of boilerplate. | | Agent workflows | Same engine through MCP, CLI, and Agent Skills. |
Built for research (benchmarks)
A blind, head-to-head test on research-oriented flows rather than plain lookups (multi-hop traces, dependency/call-graph chains, commit ranges, blast-radius, PR reviews across repositories).
How it works: 30 GitHub questions × 3 passes; Octocode vs gh, gh+Headroom, and gh+RTK on
identical questions (only the CLI differs). A blind judge (gpt-5.5) grades correctness; the metric is
characters through the model, counted from instrumented logs (characters, not tokens). Result: at
near-parity correctness, Octocode answers with ~2.0× fewer characters than plain gh, ~2.6× fewer
than gh+Headroom, and ~3.2× fewer than gh+RTK in the local-build headline runs.
▶ Open the interactive report · run it / method · questions · all reports
Tools
17 tools in the full catalog. How many register depends on the surface and the flags you set:
| Surface | Registers | What that set is |
|---|---:|---|
| MCP, no flags | 8 | GitHub search and read, plus npmSearch |
| MCP, ENABLE_LOCAL=true | 14 | Adds the five local tools and lspGetSemantics |
| MCP, + ENABLE_CLONE=true | 15 | Adds ghCloneRepo |
| MCP, + ENABLE_TOOLS allowlist | 17 | Adds ghListReleases and ghSearchDiscussions |
| CLI, no flags | 15 | Local tools and clone are on by default |
| CLI, + ENABLE_RELEASES=1 ENABLE_DISCUSSIONS=1 | 17 | Adds the same two GitHub tools |
ghListReleases and ghSearchDiscussions need two settings on MCP, not one:
ENABLE_RELEASES=1 or ENABLE_DISCUSSIONS=1 puts the tool in the catalog, and
ENABLE_TOOLS="ghListReleases,ghSearchDiscussions" registers it. Either setting
alone leaves the tool unregistered, because both carry isDefault: false and the
MCP registration filter admits only default or explicitly allowlisted tools. The
CLI needs only the ENABLE_RELEASES and ENABLE_DISCUSSIONS flags. ENABLE_LOCAL
and ENABLE_CLONE accept true or 1; ENABLE_RELEASES and ENABLE_DISCUSSIONS
also accept yes and on.
Flags: Configuration.
Token knobs. concise:true returns path/title-only lists. minify controls file read density: symbols = skeleton with line numbers, standard = comments/blanks stripped (default), none = exact bytes.
GitHub tools
| Tool | What it does | Knob |
|------|--------------|------|
| ghSearchCode | Code and path search across GitHub by owner, repository, path, filename, extension, and match filters. Accepts 1 to 5 parallel queries. | concise |
| ghGetFileContent | Read a GitHub file or region: full file, line range, match slice, or paginated chars. |
Truncated for display — read the full file on GitHub.
Related Skills
claude-mem
113.5kPersistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
Agent-Reach
109.2kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Understand-Anything
90.9kGraphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
headroom
78.9kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

