agentmako
agentmako is a local-first codebase intelligence engine that gives AI coding agents a rich, evidence-backed tool surface for understanding, navigating, and verifying a project before editing it. Key capabilities include:
Core Query & Search
reef_ask– Primary query engine: ask any project question and receive compiled code + database evidence packetscontext_packet– Turn a request into ranked, source-labeled contextlive_text_search/ast_find_pattern/cross_search– Live filesystem, structural AST, and cross-source search
Route, File & Symbol Intelligence
route_trace,file_health,auth_path,schema_usage,trace_file,trace_table,trace_rpc,trace_edge,trace_error– End-to-end tracing of routes, files, tables, RPCs, and errorssymbols_of/exports_of– List symbols declared or exported by a filepreflight_table– Full surface for a table (columns, indexes, FK, RLS, triggers, routes)
Import Graph & Dependency Analysis
imports_deps,imports_impact,imports_hotspots,imports_cycles– Map dependencies, impact, hotspots, and circular references
Graph & Flow Tools
graph_neighbors,graph_path,flow_map,change_plan– Traverse entity graphs, find paths, map flows, and plan changes
Neighborhood Composers
table_neighborhood,route_context,rpc_neighborhood– Combined context for tables, routes, and RPCs in one call
Live Database Inspection
db_ping,db_columns,db_fk,db_rls,db_rpc,db_table_schema,db_reef_refresh,db_review_comment– Inspect and annotate live DB schema, RLS, and procedures
Diagnostics
typescript_diagnostics,eslint_diagnostics,oxlint_diagnostics,biome_diagnostics,lint_files,git_precommit_check,diagnostic_refresh– Run linters and type-checkers with persisted findings
Reef Facts, Findings & Verification
project_findings,file_findings,project_facts,file_preflight,reef_verify,reef_status,reef_known_issues,project_open_loops,verification_state– Query durable findings/facts, verify completion, and surface open issuesreef_diff_impact,reef_overlay_diff,evidence_confidence,evidence_conflicts– Assess impact of changes and surface stale or contradictory evidence
Rules, Conventions & Learning
project_conventions,list_reef_rules,rule_pack_validate,extract_rule_template,reef_learning_review,reef_instructions– Surface and manage project conventions, rules, and learned patterns
Workflow & Planning
mako_help,suggest,investigate,workflow_packet,ask– Orchestrate workflows, get tool recommendations, and run bounded read-only investigations
Artifact Generators
task_preflight_artifact,implementation_handoff_artifact,review_bundle_artifact,verification_bundle_artifact– Compose structured implementation briefs, handoffs, review bundles, and verification plans
Security Audits
tenant_leak_audit– Audit tenant-keyed tables and RLS postureowasp_audit– OWASP Top 10 (2025) scan with CWE references
Session & Feedback
session_handoff,recall_answers,recall_tool_runs,agent_feedback,health_trend,issues_next– Track session state, recall prior runs, rate tool outputs, and monitor project health trends
Index & Project Management
project_index_status,project_index_refresh,repo_map,tool_batch,tool_search,file_write– Manage the project index, emit repo outlines, batch lookups, and write files (with approval)
Ingests Biome diagnostics.
Ingests ESLint diagnostics and review notes.
Ingests staged git diagnostics and provides pre-commit checks.
Provides optional Postgres/Supabase schema snapshots and read-only database inspection with review comments.
Ingests TypeScript diagnostics.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agentmakogive me a context packet for the login flow"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 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?
What You Get
MCP server for coding agents:
agentmako mcpLocal dashboard:
agentmako dashboardPrimary project query:
reef_askacross code, database, findings, diagnostics, instructions, freshness, and literal checksQueryable workflow orientation:
mako_helpDeterministic context expansion:
context_packet_hintson tool results so agents get result-specific next stepsCentral MCP annotations so clients can distinguish safe reads, live reads, and local-state mutations
Compact loop/fallback tools:
reef_status,reef_verify,reef_impact,live_text_search,lint_files, andtool_batchReef Engine facts and findings across indexed, working-tree, and staged state
Reef convention extraction for auth guards, runtime boundaries, generated paths, route patterns, and schema usage
TypeScript, ESLint, Oxlint, Biome, and staged git diagnostic ingestion
Hot-reloaded
.mako/rulesYAML rule packs, including primitive cross-file helper-bypass rules viacanonicalHelperOptional 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.
Related MCP server: Graft
Install
Requires Node.js 20 or newer.
npm install -g agentmakoConfirm the CLI is available:
agentmako --version
agentmako doctorYou 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/projectAttach and index it:
agentmako connect . --no-dbUse --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 listRun 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 "{}"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, default to reef_ask. The compact starting surface is:
reef_askfor project questions across code, database, findings, diagnostics, freshness, and quoted literal checksreef_statusfor maintained issues, changed files, stale diagnostics, and watcher/schema healthreef_verifyfor the completion gate over diagnostic freshness and open loopsreef_impactfor changed-file blast radius and convention risksmako_helpfor an ordered workflow recipe with prefilled argumentslive_text_searchfor exact current-disk regex/glob inventorieslint_filesfor bounded diagnostics and.mako/rulesfindingstool_batchfor independent read-only follow-upstool_searchto discover specialized route, graph, DB, finding, refresh, or context-expansion tools only when the compact surface points at a concrete need
4. Optional: use an agent plugin
Plain MCP works anywhere, but the bundled plugins add Mako-specific skills and
include the same agentmako mcp wiring.
Prerequisites:
Claude Code installed
Node.js 20+ on
PATH(the plugin runsnpx -y agentmako mcp, which fetches the publishedagentmakopackage automatically — no separate global install required)Your target project already attached with
agentmako connect
Claude Code stable path:
claude plugin validate .\mako-ai-claude-plugin
claude --plugin-dir .\mako-ai-claude-pluginNew 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/geminiInside 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-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 --yesThen 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 . --jsonFor 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/clinpm 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.
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-viewsFull verification:
corepack pnpm testRepository 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 skillsMore Docs
License
Apache-2.0. See LICENSE.
Maintenance
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
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