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.
Description from the maker (original English)
Local-first codebase intelligence MCP server for AI coding agents.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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": {
"agentmako": {
"command": "npx",
"args": [
"-y",
"agentmako"
]
}
}
}Run this in your terminal
claude mcp add agentmako -- npx -y agentmakoPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agentmako": {
"command": "npx",
"args": [
"-y",
"agentmako"
]
}
}
}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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"agentmako": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"agentmako"
]
}
}
}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.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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 7, 2026
The registry name was verified with the GitHub account drhalto, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed –, and the latest version (0.2.3) reached the registry 6 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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.
agentmako is a local-first codebase intelligence engine for AI coding tools.
It gives agents like Codex, Claude Code, Cursor, and local harnesses a compact Reef-first tool surface for understanding a project before they edit it. Mako indexes your repo, builds local SQLite-backed facts, tracks diagnostics and review notes, and answers evidence-backed questions instead of making the agent orchestrate broad tool chains or rediscover everything with raw grep.
Mako is built for the first mile of coding-agent work:
What files matter? What routes, symbols, tables, diagnostics, and prior
findings are relevant? What should the agent read next?
agentmako mcpagentmako dashboardreef_ask across code, database, findings, diagnostics, instructions, freshness, and literal checksmako_helpcontext_packet_hints on tool results so agents get result-specific next stepsreef_status, reef_verify, reef_impact, live_text_search, lint_files, and tool_batch.mako/rules YAML rule packs, including primitive cross-file helper-bypass rules via canonicalHelperEverything important runs locally. No hosted service is required.
Requires Node.js 20 or newer.
npm install -g agentmako
Confirm the CLI is available:
agentmako --version
agentmako doctor
You should see green checks for configuration and the local API service.
Prefer to build from source (e.g. to contribute)? See
Develop From Source at the bottom of this
file.
Go to the project you want Mako to understand:
cd C:/path/to/your/project
Attach and index it:
agentmako connect . --no-db
Use --no-db for the first run. It gets the code intelligence path working before adding database scope.
agentmako status .
agentmako tool list
Run a real Reef query:
agentmako --json tool call . reef_ask "{\"question\":\"where should I inspect auth route state?\"}"
If that returns an evidence-backed answer, facts, findings, or next queries, the core setup is working.
reef_ask plans over code, database, durable findings, diagnostics, and exact literal evidence. App-flow questions favor file, route, and finding evidence; RLS/schema questions favor database facts and review comments. To inspect project rules of thumb directly:
agentmako --json tool call . project_conventions "{}"
Add this to your MCP client config:
{
"mcpServers": { "mako-ai": { "command": "agentmako", "args": ["mcp"] } } }
Restart the MCP client and confirm the mako-ai server starts.
In the agent, default to reef_ask. The compact starting surface is:
reef_ask for project questions across code, database, findings, diagnostics, freshness, and quoted literal checksreef_status for maintained issues, changed files, stale diagnostics, and watcher/schema healthreef_verify for the completion gate over diagnostic freshness and open loopsreef_impact for changed-file blast radius and convention risksmako_help for an ordered workflow recipe with prefilled argumentslive_text_search for exact current-disk regex/glob inventorieslint_files for bounded diagnostics and .mako/rules findingstool_batch for independent read-only follow-upstool_search to discover specialized route, graph, DB, finding, refresh, or context-expansion tools only when the compact surface points at a concrete needPlain MCP works anywhere, but the bundled plugins add Mako-specific skills and include the same agentmako mcp wiring.
Prerequisites:
PATH (the plugin runs npx -y agentmako mcp, which fetches the published agentmako package automatically — no separate global install required)agentmako connectClaude Code stable path:
claude plugin validate .\mako-ai-claude-plugin
claude --plugin-dir .\mako-ai-claude-plugin
New generated plugin layouts:
claude plugin validate ./plugins/claude-code
codex marketplace add ./plugins ln -s "$(pwd)/plugins/cursor" ~/.cursor/plugins/local/mako-ai gemini extensions install ./plugins/gemini
Inside the agent, confirm the mako-ai MCP server is connected.
The plugin exposes these skills:
/mako-ai:mako-guide/mako-ai:mako-discovery/mako-ai:mako-trace/mako-ai:mako-neighborhoods/mako-ai:mako-graph/mako-ai:mako-database/mako-ai:mako-code-intel/mako-ai:mako-workflowUse the plugin when you want Claude Code to load Mako-specific guidance for which tools to call and how to interpret their results.
From your target project:
agentmako dashboard .
This starts the local API, harness service, and web dashboard.
Mako works without a database. Add this only after code intelligence is working.
For a one-time interactive setup:
agentmako connect .
For CI or scripted setup using an environment variable:
set DATABASE_URL=postgres://...
agentmako connect . --db-env DATABASE_URL --yes
Then refresh and verify the local schema snapshot:
agentmako refresh .
agentmako verify .
Interactive mode stores database secrets in your OS keychain by default. Project config stores references, not plaintext DB URLs.
From the target project:
agentmako status .
agentmako dashboard . agentmako --json tool call . context_packet "{\"query\":\"fix the broken auth callback route\"}"
For staged review checks:
agentmako git precommit . --json
For database review notes:
agentmako --json tool call . db_review_comment "{\"objectType\":\"replication\",\"objectName\":\"supabase_database_replication\",\"category\":\"review\",\"comment\":\"Check publication coverage before relying on realtime events.\",\"tags\":[\"supabase\",\"replication\"]}"
If you want to hack on Mako itself, clone and build instead of installing from npm.
Prerequisites:
corepack enable, included with modern Node.js)git clone https://github.com/drhalto/agentmako.git
cd agentmako corepack pnpm install corepack pnpm run build npm link ./apps/cli
npm link ./apps/cli makes the source-built CLI available as agentmako on your PATH, replacing any global npm install. Re-run corepack pnpm run build after pulling changes.
To go back to the published version: npm install -g agentmako.
corepack pnpm run typecheck
corepack pnpm run build corepack pnpm run test:smoke:reef-tooling corepack pnpm run test:smoke:reef-model-facing-views
Full verification:
corepack pnpm test
apps/
cli/ agentmako CLI and MCP entrypoint (the published package) web/ local dashboard packages/ contracts/ public TypeScript contracts and tool schemas config/ shared config helpers logger/ shared logger sdk/ programmatic SDK store/ SQLite stores, migrations, and query helpers tools/ shared tool implementations harness-core/ local agent harness runtime harness-tools/ action tools available to the harness harness-contracts/ harness contracts and provider catalog services/ api/ local API and MCP transports engine/ Reef Engine fact/finding pipeline harness/ local harness HTTP service indexer/ repo and schema indexing logic worker/ background worker extensions/ provider and integration packages storage/ schema migrations, models, queries test/smoke/ smoke coverage mako-ai-claude-plugin/ Claude Code plugin with Mako skills
Apache-2.0. See LICENSE.