agentmako
Health Uyari
- License — License: Apache-2.0
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 6 GitHub stars
Code Uyari
- network request — Outbound network request in apps/cli/scripts/snapshot-models.ts
- process.env — Environment variable access in apps/cli/src/commands/connect.ts
- process.env — Environment variable access in apps/cli/src/commands/dashboard.ts
- network request — Outbound network request in apps/cli/src/commands/dashboard.ts
Permissions Gecti
- Permissions — No dangerous permissions requested
This is a local-first codebase intelligence engine that gives AI coding tools a structured context about a project. It indexes your codebase, tracks diagnostics, and stores code facts in a local SQLite database so your AI assistant can understand your project before editing it.
Security Assessment
Overall risk: Low. The server explicitly states that everything important runs locally and no hosted service is required. The code does make outbound network requests, but these appear to be limited to an optional script for taking Postgres/Supabase database schema snapshots and serving a local dashboard. There are no hardcoded secrets. Environment variable access is used appropriately for configuration via the command-line interface rather than maliciously exfiltrating data. No dangerous system permissions are requested, and it does not seem to execute arbitrary hidden shell commands. The only real caution is that the tool inherently reads and indexes your local source code, so ensure you trust the environment where you run it.
Quality Assessment
The project is actively maintained, with its most recent push happening today. It uses a standard, permissive open-source license (Apache-2.0) and includes automated smoke tests. However, community trust and visibility are currently very low. With only 6 GitHub stars, it is a very new or niche project, meaning bugs or edge cases might not yet be fully vetted by a wider audience.
Verdict
Safe to use, but be aware of its early-stage maturity and review the code yourself if you plan to connect it to sensitive production databases.
Local-first MCP server that gives coding agents structured context packets, code/schema facts, and diagnostics - backed by a local SQLite store.
agentmako
agentmako is a local-first codebase intelligence engine for AI coding
tools.
It gives agents like Codex, Claude Code, Cursor, and local harnesses a
typed MCP toolset for understanding a project before they edit it. Mako
indexes your repo, builds local SQLite-backed facts, tracks diagnostics
and review notes, and returns structured context packets instead of
making the agent 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?
What You Get
- MCP server for coding agents:
agentmako mcp - Local dashboard:
agentmako dashboard - Deterministic context packets:
context_packet,reef_scout - Code search and structure tools:
cross_search,live_text_search,ast_find_pattern,repo_map - Reef Engine facts and findings across indexed,
working-tree, and staged state - TypeScript, ESLint, Oxlint, Biome, and staged git diagnostic ingestion
- Optional Postgres/Supabase schema snapshots and read-only DB inspection
- Local DB review comments for notes on tables, RLS, triggers,
publications, subscriptions, and replication - Recall, acknowledgements, and agent feedback for repeated review work
Everything important runs locally. No hosted service is required.
Install
Requires Node.js 20 or newer.
npm install -g agentmako
Confirm the CLI is available:
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.
Happy Path Setup
1. Attach your real project
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.
2. Confirm Mako sees the project
agentmako status .
agentmako tool list
Run a real scout query:
agentmako --json tool call . reef_scout "{\"query\":\"where should I inspect auth route state?\"}"
If that returns ranked candidates, facts, or findings, the core setup is
working.
3. Configure your MCP client
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, start with one of these tools:
tool_searchwhen you need to find the right Mako toolcontext_packetwhen you have a coding task and want starting contextreef_scoutwhen you want ranked project facts/findings/historyaskwhen you have a natural-language repo question
4. Optional: use the Claude Code plugin
Plain MCP works with Claude Code, but the bundled plugin adds Mako-specific
Claude skills and includes the same agentmako mcp wiring inmako-ai-claude-plugin/.mcp.json.
Prerequisites:
- Claude Code installed
agentmakoavailable onPATH- Your target project already attached with
agentmako connect
From the agentmako repo root:
claude plugin validate .\mako-ai-claude-plugin
claude --plugin-dir .\mako-ai-claude-plugin
Inside Claude Code, run /mcp and confirm mako-ai 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-workflow
Use the plugin when you want Claude Code to load Mako-specific guidance for
which tools to call and how to interpret their results.
5. Optional: launch the dashboard
From your target project:
agentmako dashboard .
This starts the local API, harness service, and web dashboard.
6. Optional: add Supabase/Postgres awareness
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.
Normal Daily Loop
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\"]}"
Develop From Source
If you want to hack on Mako itself, clone and build instead of installing
from npm.
Prerequisites:
- Node.js 20 or newer
- Git
- Corepack (
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 asagentmako on your PATH, replacing any global npm install. Re-runcorepack pnpm run build after pulling changes.
To go back to the published version: npm install -g agentmako.
Development Checks
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
Repository Layout
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
More Docs
- Tool overview
- CLI docs
- Reef Engine
- Claude Code plugin
- Agent guidance to paste into CLAUDE.md / AGENTS.md
- Contributing
- Security policy
- Changelog
License
Apache-2.0. See LICENSE.
Yorumlar (0)
Yorum birakmak icin giris yap.
Yorum birakSonuc bulunamadi