Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
AI governance MCP server — policy enforcement, skills, memory, multi-LLM consensus
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.
AGENCE_ROOTYou 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": {
"agence": {
"command": "npx",
"args": [
"-y",
"@l-agence/mcp-server-agence"
],
"env": {
"AGENCE_ROOT": "your-value"
}
}
}
}Run this in your terminal
claude mcp add agence --env AGENCE_ROOT=your-value -- npx -y @l-agence/mcp-server-agenceFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agence": {
"command": "npx",
"args": [
"-y",
"@l-agence/mcp-server-agence"
],
"env": {
"AGENCE_ROOT": "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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"agence": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@l-agence/mcp-server-agence"
],
"env": {
"AGENCE_ROOT": "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.
AGENCE_ROOT envThese 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 8, 2026
The registry name was verified with the GitHub account l-agence, 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 (1.0.0) 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: Context7, Codebase Memory, Exa
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
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
Author: Stephane Korning · 2026 · MIT + Commons Clause Version: v1.0.0 · May 2026
The governance layer for AI coding agents.
Every agent action classified, gated, and cryptographically logged — regardless of which LLM or tool runs it.
Your AI coding agents can write code. They can commit, push, delete, refactor.
But who's watching them?
Claude Code has no audit trail. Aider trusts the user. Codex sandboxes everything and hopes for the best. LangChain gives you building blocks but no guardrails.
Agence exists because advisory guardrails aren't guardrails at all. It's the layer that sits between any AI agent and your filesystem and says *"not without approval."*
Agence is an agent-agnostic governance stack for software engineering. It doesn't replace your coding agent — it governs, orchestrates, and audits all of them from a single control plane.
Command Gating — Every shell command is classified before execution:
| Tier | Gate | Example |
|---|---|---|
| T0 | Auto-execute | git status, ls, cat |
| T1 | Logged | git add, git commit |
| T2 | Human approval required | git push, git reset |
| T3 | Blocked | rm -rf, chmod 777, kill |
Unknown commands default to T2. Not T0. Fail-closed. The guard runs as a separate process — agents cannot bypass their own policy.
Cryptographic Audit — Every agent decision is logged to a Merkle-chained, append-only ledger. Each entry links to the previous via SHA-256. Tamper with one entry and the chain breaks. Verify with: agence ^ledger verify.
Multi-Agent Orchestration — 18 agents across 4 types (persona, tool, loop, ensemble). Route with @agent syntax. Override models with dot-notation: @ralph.gpt4o. Dispatch to Aider, Claude Code, Copilot, or your own tools — all governed by the same policy.
Peer Consensus — Route any question to 3 independent LLMs and get weighted consensus. Your architecture review shouldn't depend on one model's blind spots.
Session Persistence — Save, resume, and hand off sessions between agents. Full context survives restarts. Automatic tmux capture of stdout/stdin/stderr — no 16KB buffer limits.
Git-Native — No database. No server. State lives in git worktrees and flat files. Knowledge is sharded, gated, and selectively routed — you decide what gets shared.
| 30,701 | Lines of production code (23.9K TypeScript + 6.8K bash) |
| 751 | Tests with 1,768 assertions across 21 files |
| 279 | Security-specific tests (guard + hardening + SEC regressions) |
| 9 | Red-team cycles completed (SEC-008 through SEC-019) |
| 33+ | Orchestration skills (^fix, ^review, ^hack, ^peers, ^vault...) |
| 18 | Registered agents (10 persona, 5 tool, 1 loop, 2 ensemble) |
| 12 | LLM providers (Anthropic, OpenAI, Azure, Google, Mistral, Groq, Ollama...) |
| 10 | MCP tools + 3 MCP resources (Model Context Protocol server) |
| 3 | Dependencies total (MCP SDK, Bun, Zod) |
| 0 | Databases required |
rm -rfAgence governs all of the above.
Gate AI agent commands in any CI workflow — one step, zero infrastructure:
- name: Gate AI command
id: guard uses: l-agence/agence@v1 with: command: 'git push origin main' # command proposed by your AI agent agent: ci fail_on_block: 'true' # fail if T3-blocked
| Input | Description | Default |
|---|---|---|
command | Shell command to classify | required |
policy | Path to custom AIPOLICY.yaml (repo-relative) | bundled policy |
agent | Agent identity for MLS capability checks | ci |
fail_on_block | Exit 1 on T3 (deny) | true |
fail_on_escalate | Exit 1 on T2 (requires approval) | false |
| Output | Values |
|---|---|
tier | T0 · T1 · T2 · T3 |
action | allow · flag · escalate · deny |
reason | Human-readable decision |
rule | Matched policy rule |
See docs/marketplace/description.md for full documentation.
This PR starts with the GitHub Action path first for fast per-repo adoption; the GitHub App listing and webhook server can follow in a later phase or separate PR for org-level rollout across many repositories.
For enterprise adoption, the next layer after the GitHub App is shard onboarding so orgs can separate teams, policies, and knowledge boundaries cleanly instead of forcing one shared shard model.
git submodule add https://github.com/l-agence/agence .agence
git submodule update --init --recursive bash .agence/bin/agence ^init export PATH="$PWD/.agence/bin:$PATH"
git clone https://github.com/l-agence/agence .agence
cd .agence && bun install ./bin/agence ^init export PATH="$PWD/.agence/bin:$PATH"
| Tool | Required | Install |
|---|---|---|
bash 4+ | Yes | Built-in on Linux/macOS/WSL |
git 2.30+ | Yes | sudo apt install git |
bun 1.3+ | Yes | bun.sh |
tmux | For swarm | sudo apt install tmux |
jq | For ledger queries | sudo apt install jq |
Windows: Use WSL (Ubuntu recommended).
# Chat with an agent
agence "How should I structure this feature?"
agence @sonya "Review this auth module"
agence !ralph # Persona: autonomous iteration agence !claude # Tool: Claude Code CLI agence !aider # Tool: aider (code patches)
agence ^save "OAuth2: done token validation, next: refresh flow" agence ^resume agence ^handoff @sonya
agence ^ledger verify # Verify Merkle chain integrity agence ^audit trail # View full decision history
agence @peers "Should we use Redis or Postgres for session storage?"
agence --help
YOUR REPO/
└── .agence/ ← lives here (submodule or clone) ├── bin/ # CLI: agence, aibash, ibash, aido, agentd ├── codex/ # Governance: AIPOLICY.yaml, Laws, Principles, agents/ ├── nexus/ # Local state: .ailedger, sessions, faults (gitignored) ├── knowledge/ # Team knowledge: docs, lessons, plans (committed) │ └── private/ # Private knowledge (gitignored, never shared) ├── organic/ # Swarm coordination: tasks, jobs, workflows └── lib/ # Core: guard.ts, signal.ts, skill.ts, memory.ts, peers.ts
COGNOS — Four pillars:
| Pillar | Purpose | Location |
|---|---|---|
| CODEX | Immutable governance — Laws, Principles, Rules, AIPOLICY | codex/ |
| KNOWLEDGE | Team-shared docs, lessons, plans — selectively routed via @ symlinks | knowledge/ |
| NEXUS | Local operational state — sessions, ledger, signals | nexus/ (gitignored) |
| ORGANIC | Swarm orchestration — tasks, workflows, matrix scheduling | organic/ |
Runtime: Bun + bash. No Python. No pip. No npm install of untrusted packages in the critical path.
MCP: Agence exposes itself as an MCP server (10 tools, 3 resources) so any MCP-compatible client can use agence's governance layer. Agence also acts as an MCP client — consuming tools from external MCP servers. See MCP.md for integration guide.
| Prefix | Mode | Example | Use When |
|---|---|---|---|
| _(none)_ | Chat | agence "explain this error" | Advice, explanation, Q&A |
^ | Knowledge | agence ^save, agence ^lesson | Shared state, knowledge ops |
~ | Private | agence ~note "idea" | Private notes (never committed) |
+ | Autonomous | agence +refactor-auth | Agent plans & executes a task |
/ | Validated | agence /git-status | Pre-approved safe commands |
! | System | agence !ralph, agence !claude | Launch agents or tools |
@ | Route | agence @sonya "review this" | Send to specific agent |
| Agent | Type | Best For |
|---|---|---|
@ralph | Loop | Autonomous iteration with backpressure |
@sonya | Persona | Architecture, code review |
@claudia | Persona | Deep reasoning, critical decisions |
@chad | Persona | DevOps, infra, CI/CD |
@aleph | Persona | Red team, security analysis |
@claude | Tool | Claude Code CLI (headless spawn) |
@aider | Tool | Code patches, git diffs |
@pilot | Tool | GitHub Copilot CLI |
@peers | Ensemble | 3-LLM weighted consensus |
@pair | Ensemble | 2-LLM lightweight consensus |
Override models with dot-notation: @ralph.gpt4o, @sonya.opus, @ralph.aider
Agence uses a 5-tier command policy. The guard runs as a separate process — agents cannot bypass their own policy.
| Tier | Gate | Example |
|---|---|---|
| T0 | Auto-execute | git status, ls, cat |
| T1 | Logged | git add, git commit |
| T2 | Human approval | git push, git reset |
| T3 | Blocked | rm -rf, chmod 777 |
| T4 | Never | Force push main, drop DB |
Unknown commands default to T2. Fail-closed. 120+ rules across git, GitHub CLI, AWS, Terraform, and shell.
All decisions logged to nexus/.ailedger — append-only, Merkle-chained, HMAC-signed.
See SECURITY.md for full security architecture, red-team findings, and disclosure timeline.
agentd start ralph claude aider # Launch 3 agents in tmux
agentd tangent create fix-auth # Isolated worktree + container agentd inject fix-auth "run tests" # Send command via socat socket agentd status # View all agents + tangents
Each tangent gets: isolated git worktree, optional Docker container (--cap-drop ALL, --read-only, --no-new-privileges), socat socket for IPC, tmux pane for observability.
bun test # Full suite
751 tests, 1,768 assertions, 0 failures across 21 files:
| Suite | Tests | Coverage |
|---|---|---|
guard.test.ts | 132 | Command gate, tier escalation, eval safety |
security-hardening.test.ts | 134 | HMAC, signal forgery, injection prevention, SEC-010→019 regressions |
memory.test.ts | 62 | COGNOS 3-store: retain/recall/cache/forget/promote/distill |
peers-dispatch.test.ts | 53 | Peer consensus, mixed routing |
queue.test.ts | 42 | Work queue, dashboard, GitHub Issues bridge |
runs.test.ts | 35 | SWE run lifecycle, aggregation, outcomes |
vault.test.ts | 20 | Hermetic vault init/sync/push/pull + SEC-019 security |
setup.test.ts | 10 | Interactive wizard, escaping, validation |
| mcp-client.test.ts
Only the beginning is shown; read the rest in the repo