Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Octocode MCP - AI Context Platform

by bgauryyversion 7.0.9i★ –iRuns on your computer
Registry nameio.github.bgauryy/octocode-mcp

Install

Overview

Description from the maker (original English)

AI code research platform. Search, analyze, and extract insights from any GitHub repository.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools
  • You need to fill in: GITHUB_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: GITHUB_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": [
        "-y",
        "octocode-mcp"
      ],
      "env": {
        "GITHUB_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add octocode --env GITHUB_TOKEN=your-value -- npx -y octocode-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "octocode": {
      "command": "npx",
      "args": [
        "-y",
        "octocode-mcp"
      ],
      "env": {
        "GITHUB_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "octocode": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "octocode-mcp"
      ],
      "env": {
        "GITHUB_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • GITHUB_TOKEN secret env
    GitHub Personal Access Token. Optional - authenticate via GitHub CLI (gh auth login) for automatic token management, or set this token manually for CI/CD environments.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account bgauryy, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 5547 servers in this category
  • Published to the registry more recently than 1% of the other 5547 servers in this category
  • Basic checks equal to or better than 100% of the other 5547 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Octocode MCP - AI Context Platform safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GITHUB_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (7.0.9) reached the registry 12 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

GitHub

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

by githubWidely used★ 34.2KUpdated 5 days ago

Computer or cloud

Desktop Commander

MCP server for terminal commands, file operations, and process management

by wonderwhy-erWidely used↓ 709.6K/wk★ 10.2KUpdated 17 days ago

Runs on your computer

Cloudflare MCP

Cloudflare MCP servers

by cloudflareWidely used★ 4.4KUpdated 14 months ago

Runs in the cloud✓ mcp.cloudflare.com

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Octocode: agentic research platform

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:

Show more install options (Windsurf, Kiro, Goose, LM Studio, Claude Code)

Claude Code:

claude mcp add-json octocode --scope user '{"command":"npx","type":"stdio","args":["octocode-mcp@latest"]}'

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}'

```yaml

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](https://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):

NeedUse Octocode to
Codebase questionsSearch local or GitHub code, read exact regions, browse trees, and carry file/line anchors into the answer.
Implementation researchCompare patterns across repositories, npm packages, pull requests, commits, and local files before changing code.
Semantic navigationResolve definitions, references, callers/callees, call hierarchy, hovers, symbols, diagnostics, and type relationships through LSP.
Structural matchingRun AST-shaped searches with patterns or YAML rules so comments and strings do not become false positives.
Large-file contextMinify, skeletonize, or paginate code so agents spend tokens on relevant structure instead of boilerplate.
Agent workflowsSame 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](https://raw.githack.com/bgauryy/octocode/main/packages/octocode-benchmark/results/index.html) · [run it / method](https://github.com/bgauryy/octocode/tree/main/packages/octocode-benchmark/skills/octocode-benchmark) · questions · all reports


Tools

17 tools in the full catalog. How many register depends on the surface and the flags you set:

SurfaceRegistersWhat that set is
MCP, no flags8GitHub search and read, plus npmSearch
MCP, ENABLE_LOCAL=true14Adds the five local tools and lspGetSemantics
MCP, + ENABLE_CLONE=true15Adds ghCloneRepo
MCP, + ENABLE_TOOLS allowlist17Adds ghListReleases and ghSearchDiscussions
CLI, no flags15Local tools and clone are on by default
CLI, + ENABLE_RELEASES=1 ENABLE_DISCUSSIONS=117Adds 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
ToolWhat it doesKnob
ghSearchCodeCode and path search across GitHub by owner, repository, path, filename, extension, and match filters. Accepts 1 to 5 parallel queries.concise
ghGetFileContentRead a GitHub file or region: full file, line range, match slice, or paginated chars.

Only the beginning is shown; read the rest in the repo

Ask PopNx