agentmako

Name: agentmako
Author: drhalto

bydrhalto· 1 MCP server

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How to install agentmako?

drhalto/agentmako

$git clone https://github.com/drhalto/agentmako

Installs into the current project.

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Install & use

Install agentmako by running `git clone https://github.com/drhalto/agentmako`, then use it for the current task and follow its documentation at https://github.com/drhalto/agentmako.

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README.md

1	<p align="center">
2	<img src="apps/web/public/agentmako.png" alt="agentmako logo" width="180" />
3	</p>
4
5	# agentmako
6
7	[![npm version](https://img.shields.io/npm/v/agentmako.svg?logo=npm)](https://www.npmjs.com/package/agentmako)
8	[![Smoke Tests](https://github.com/drhalto/agentmako/actions/workflows/smoke.yml/badge.svg)](https://github.com/drhalto/agentmako/actions/workflows/smoke.yml)
9	[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE)
10	[![Node.js >=20](https://img.shields.io/badge/node-%3E%3D20-brightgreen.svg)](https://nodejs.org/)
11	[![agentmako MCP server](https://glama.ai/mcp/servers/drhalto/agentmako/badges/score.svg)](https://glama.ai/mcp/servers/drhalto/agentmako)
12
13	agentmako is a local-first codebase intelligence engine for AI coding
14	tools.
15
16	It gives agents like Codex, Claude Code, Cursor, and local harnesses a
17	compact Reef-first tool surface for understanding a project before they edit
18	it. Mako indexes your repo, builds local SQLite-backed facts, tracks
19	diagnostics and review notes, and answers evidence-backed questions instead of
20	making the agent orchestrate broad tool chains or rediscover everything with
21	raw grep.
22
23	Mako is built for the first mile of coding-agent work:
24
25	> What files matter? What routes, symbols, tables, diagnostics, and prior
26	> findings are relevant? What should the agent read next?
27
28	## What You Get
29
30	- MCP server for coding agents: `agentmako mcp`
31	- Local dashboard: `agentmako dashboard`
32	- Primary project query: `reef_ask` across code, database, findings,
33	diagnostics, instructions, freshness, and literal checks
34	- Queryable workflow orientation: `mako_help`
35	- Deterministic context expansion: `context_packet`
36	- `_hints` on tool results so agents get result-specific next steps
37	- Central MCP annotations so clients can distinguish safe reads, live reads,
38	and local-state mutations
39	- Compact loop/fallback tools: `reef_status`, `reef_verify`, `reef_impact`,
40	`live_text_search`, `lint_files`, and `tool_batch`
41	- [Reef Engine](./docs/reef-engine.md) facts and findings across indexed,
42	working-tree, and staged state
43	- Reef convention extraction for auth guards, runtime boundaries, generated
44	paths, route patterns, and schema usage
45	- TypeScript, ESLint, Oxlint, Biome, and staged git diagnostic ingestion
46	- Hot-reloaded `.mako/rules` YAML rule packs, including primitive
47	cross-file helper-bypass rules via `canonicalHelper`
48	- Optional Postgres/Supabase schema snapshots and read-only DB inspection
49	- Local DB review comments for notes on tables, RLS, triggers,
50	publications, subscriptions, and replication
51	- Recall, acknowledgements, and agent feedback for repeated review work
52
53	Everything important runs locally. No hosted service is required.
54
55	## Install
56
57	Requires Node.js 20 or newer.
58
59	```bash
60	npm install -g agentmako
61	```
62
63	Confirm the CLI is available:
64
65	```bash
66	agentmako --version
67	agentmako doctor
68	```
69
70	You should see green checks for configuration and the local API service.
71
72	> Prefer to build from source (e.g. to contribute)? See
73	> [Develop From Source](#develop-from-source) at the bottom of this
74	> file.
75
76	## Happy Path Setup
77
78	### 1. Attach your real project
79
80	Go to the project you want Mako to understand:
81
82	```bash
83	cd C:/path/to/your/project
84	```
85
86	Attach and index it:
87
88	```bash
89	agentmako connect . --no-db
90	```
91
92	Use `--no-db` for the first run. It gets the code intelligence path
93	working before adding database scope.
94
95	### 2. Confirm Mako sees the project
96
97	```bash
98	agentmako status .
99	agentmako tool list
100	```
101
102	Run a real Reef query:
103
104	```bash
105	agentmako --json tool call . reef_ask "{\"question\":\"where should I inspect auth route state?\"}"
106	```
107
108	If that returns an evidence-backed answer, facts, findings, or next queries,
109	the core setup is working.
110
111	`reef_ask` plans over code, database, durable findings, diagnostics, and exact
112	literal evidence. App-flow questions favor file, route, and finding evidence;
113	RLS/schema questions favor database facts and review comments. To inspect
114	project rules of thumb directly:
115
116	```bash
117	agentmako --json tool call . project_conventions "{}"
118	```
119
120	### 3. Configure your MCP client
121
122	Add this to your MCP client config:
123
124	```json
125	{
126	"mcpServers": {
127	"mako-ai": {
128	"command": "agentmako",
129	"args": ["mcp"]
130	}
131	}
132	}
133	```
134
135	Restart the MCP client and confirm the `mako-ai` server starts.
136
137	In the agent, default to `reef_ask`. The compact starting surface is:
138
139	- `reef_ask` for project questions across code, database, findings,
140	diagnostics, freshness, and quoted literal checks
141	- `reef_status` for maintained issues, changed files, stale diagnostics, and
142	watcher/schema health
143	- `reef_verify` for the completion gate over diagnostic freshness and open loops
144	- `reef_impact` for changed-file blast radius and convention risks
145	- `mako_help` for an ordered workflow recipe with prefilled arguments
146	- `live_text_search` for exact current-disk regex/glob inventories
147	- `lint_files` for bounded diagnostics and `.mako/rules` findings
148	- `tool

6 picks

Type

agentmako

bydrhalto· 1 MCP server

Stars

Forks

How to install agentmako?

drhalto/agentmako

$git clone https://github.com/drhalto/agentmako

Installs into the current project.

›Prefer a prompt? Paste this to your agent

Install & use

Install agentmako by running `git clone https://github.com/drhalto/agentmako`, then use it for the current task and follow its documentation at https://github.com/drhalto/agentmako.

Files · 1

View on GitHub

README.md

1	<p align="center">
2	<img src="apps/web/public/agentmako.png" alt="agentmako logo" width="180" />
3	</p>
4
5	# agentmako
6
7	[![npm version](https://img.shields.io/npm/v/agentmako.svg?logo=npm)](https://www.npmjs.com/package/agentmako)
8	[![Smoke Tests](https://github.com/drhalto/agentmako/actions/workflows/smoke.yml/badge.svg)](https://github.com/drhalto/agentmako/actions/workflows/smoke.yml)
9	[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE)
10	[![Node.js >=20](https://img.shields.io/badge/node-%3E%3D20-brightgreen.svg)](https://nodejs.org/)
11	[![agentmako MCP server](https://glama.ai/mcp/servers/drhalto/agentmako/badges/score.svg)](https://glama.ai/mcp/servers/drhalto/agentmako)
12
13	agentmako is a local-first codebase intelligence engine for AI coding
14	tools.
15
16	It gives agents like Codex, Claude Code, Cursor, and local harnesses a
17	compact Reef-first tool surface for understanding a project before they edit
18	it. Mako indexes your repo, builds local SQLite-backed facts, tracks
19	diagnostics and review notes, and answers evidence-backed questions instead of
20	making the agent orchestrate broad tool chains or rediscover everything with
21	raw grep.
22
23	Mako is built for the first mile of coding-agent work:
24
25	> What files matter? What routes, symbols, tables, diagnostics, and prior
26	> findings are relevant? What should the agent read next?
27
28	## What You Get
29
30	- MCP server for coding agents: `agentmako mcp`
31	- Local dashboard: `agentmako dashboard`
32	- Primary project query: `reef_ask` across code, database, findings,
33	diagnostics, instructions, freshness, and literal checks
34	- Queryable workflow orientation: `mako_help`
35	- Deterministic context expansion: `context_packet`
36	- `_hints` on tool results so agents get result-specific next steps
37	- Central MCP annotations so clients can distinguish safe reads, live reads,
38	and local-state mutations
39	- Compact loop/fallback tools: `reef_status`, `reef_verify`, `reef_impact`,
40	`live_text_search`, `lint_files`, and `tool_batch`
41	- [Reef Engine](./docs/reef-engine.md) facts and findings across indexed,
42	working-tree, and staged state
43	- Reef convention extraction for auth guards, runtime boundaries, generated
44	paths, route patterns, and schema usage
45	- TypeScript, ESLint, Oxlint, Biome, and staged git diagnostic ingestion
46	- Hot-reloaded `.mako/rules` YAML rule packs, including primitive
47	cross-file helper-bypass rules via `canonicalHelper`
48	- Optional Postgres/Supabase schema snapshots and read-only DB inspection
49	- Local DB review comments for notes on tables, RLS, triggers,
50	publications, subscriptions, and replication
51	- Recall, acknowledgements, and agent feedback for repeated review work
52
53	Everything important runs locally. No hosted service is required.
54
55	## Install
56
57	Requires Node.js 20 or newer.
58
59	```bash
60	npm install -g agentmako
61	```
62
63	Confirm the CLI is available:
64
65	```bash
66	agentmako --version
67	agentmako doctor
68	```
69
70	You should see green checks for configuration and the local API service.
71
72	> Prefer to build from source (e.g. to contribute)? See
73	> [Develop From Source](#develop-from-source) at the bottom of this
74	> file.
75
76	## Happy Path Setup
77
78	### 1. Attach your real project
79
80	Go to the project you want Mako to understand:
81
82	```bash
83	cd C:/path/to/your/project
84	```
85
86	Attach and index it:
87
88	```bash
89	agentmako connect . --no-db
90	```
91
92	Use `--no-db` for the first run. It gets the code intelligence path
93	working before adding database scope.
94
95	### 2. Confirm Mako sees the project
96
97	```bash
98	agentmako status .
99	agentmako tool list
100	```
101
102	Run a real Reef query:
103
104	```bash
105	agentmako --json tool call . reef_ask "{\"question\":\"where should I inspect auth route state?\"}"
106	```
107
108	If that returns an evidence-backed answer, facts, findings, or next queries,
109	the core setup is working.
110
111	`reef_ask` plans over code, database, durable findings, diagnostics, and exact
112	literal evidence. App-flow questions favor file, route, and finding evidence;
113	RLS/schema questions favor database facts and review comments. To inspect
114	project rules of thumb directly:
115
116	```bash
117	agentmako --json tool call . project_conventions "{}"
118	```
119
120	### 3. Configure your MCP client
121
122	Add this to your MCP client config:
123
124	```json
125	{
126	"mcpServers": {
127	"mako-ai": {
128	"command": "agentmako",
129	"args": ["mcp"]
130	}
131	}
132	}
133	```
134
135	Restart the MCP client and confirm the `mako-ai` server starts.
136
137	In the agent, default to `reef_ask`. The compact starting surface is:
138
139	- `reef_ask` for project questions across code, database, findings,
140	diagnostics, freshness, and quoted literal checks
141	- `reef_status` for maintained issues, changed files, stale diagnostics, and
142	watcher/schema health
143	- `reef_verify` for the completion gate over diagnostic freshness and open loops
144	- `reef_impact` for changed-file blast radius and convention risks
145	- `mako_help` for an ordered workflow recipe with prefilled arguments
146	- `live_text_search` for exact current-disk regex/glob inventories
147	- `lint_files` for bounded diagnostics and `.mako/rules` findings
148	- `tool

6 picks

Type

agentmako

How to install agentmako?

Related

agentmako

How to install agentmako?

Related