Agence
Provides a GitHub Action for gating AI agent commands in CI pipelines and integrates with GitHub Copilot.
Enables use of GitHub Copilot CLI as a tool agent for code suggestions.
Allows AI agents to leverage Google AI (Gemini) models for reasoning.
Allows AI agents to use locally hosted LLMs via Ollama.
Allows AI agents to use OpenAI models (e.g., GPT-4) for reasoning.
Integrates with HashiCorp Vault for secure secret storage and retrieval, accessible via the '^vault' skill.
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., "@AgenceClassify 'git push origin main'"
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.
l'Agence — Agentic Engineering Co-Environments
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.
The Problem
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."
Related MCP server: kontexta
What Agence Does
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 |
|
T1 | Logged |
|
T2 | Human approval required |
|
T3 | Blocked |
|
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.
By the Numbers
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 ( |
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 |
Who This Is For
Teams using multiple AI coding agents who need one policy governing all of them
Enterprises requiring audit trails for AI-generated code changes
Security-conscious developers who want fail-closed gating, not fail-open trust
Anyone who's had an AI agent break something and wished there was a layer between the agent and
rm -rf
Who This Is NOT For
If you want an AI pair programmer → use Aider
If you want IDE autocomplete → use Continue or Copilot
If you want to build any kind of agent → use LangChain/LangGraph
If you want cloud-hosted async tasks → use OpenAI Codex
Agence governs all of the above.
GitHub Action — Agence Guard
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
- run: echo "Tier ${{ steps.guard.outputs.tier }} — ${{ steps.guard.outputs.reason }}"Input | Description | Default |
| Shell command to classify | required |
| Path to custom | bundled policy |
| Agent identity for MLS capability checks |
|
| Exit 1 on T3 (deny) |
|
| Exit 1 on T2 (requires approval) |
|
Output | Values |
|
|
|
|
| Human-readable decision |
| Matched policy rule |
See docs/marketplace/description.md for full documentation.
This PR starts with the GitHub Action path first for fast per-repo adoption; the GitHub App listing and webhook server can follow in a later phase or separate PR for org-level rollout across many repositories.
For enterprise adoption, the next layer after the GitHub App is shard onboarding so orgs can separate teams, policies, and knowledge boundaries cleanly instead of forcing one shared shard model.
Install
As a git submodule (recommended)
git submodule add https://github.com/l-agence/agence .agence
git submodule update --init --recursive
bash .agence/bin/agence ^init
export PATH="$PWD/.agence/bin:$PATH"Or: clone directly
git clone https://github.com/l-agence/agence .agence
cd .agence && bun install
./bin/agence ^init
export PATH="$PWD/.agence/bin:$PATH"Prerequisites
Tool | Required | Install |
| Yes | Built-in on Linux/macOS/WSL |
| Yes |
|
| Yes | |
| For swarm |
|
| For ledger queries |
|
Windows: Use WSL (Ubuntu recommended).
Quick Start
# Chat with an agent
agence "How should I structure this feature?"
# Route to a specific agent
agence @sonya "Review this auth module"
# Launch an agent shell
agence !ralph # Persona: autonomous iteration
agence !claude # Tool: Claude Code CLI
agence !aider # Tool: aider (code patches)
# Save session (resume later or hand off to another agent)
agence ^save "OAuth2: done token validation, next: refresh flow"
agence ^resume
agence ^handoff @sonya
# Audit trail
agence ^ledger verify # Verify Merkle chain integrity
agence ^audit trail # View full decision history
# Peer consensus (3 independent LLMs)
agence @peers "Should we use Redis or Postgres for session storage?"
# See all commands
agence --helpArchitecture
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.tsCOGNOS — Four pillars:
Pillar | Purpose | Location |
CODEX | Immutable governance — Laws, Principles, Rules, AIPOLICY |
|
KNOWLEDGE | Team-shared docs, lessons, plans — selectively routed via |
|
NEXUS | Local operational state — sessions, ledger, signals |
|
ORGANIC | Swarm orchestration — tasks, workflows, matrix scheduling |
|
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.
Command Reference
Prefix | Mode | Example | Use When |
(none) | Chat |
| Advice, explanation, Q&A |
| Knowledge |
| Shared state, knowledge ops |
| Private |
| Private notes (never committed) |
| Autonomous |
| Agent plans & executes a task |
| Validated |
| Pre-approved safe commands |
| System |
| Launch agents or tools |
| Route |
| Send to specific agent |
Agent Roster
Agent | Type | Best For |
| Loop | Autonomous iteration with backpressure |
| Persona | Architecture, code review |
| Persona | Deep reasoning, critical decisions |
| Persona | DevOps, infra, CI/CD |
| Persona | Red team, security analysis |
| Tool | Claude Code CLI (headless spawn) |
| Tool | Code patches, git diffs |
| Tool | GitHub Copilot CLI |
| Ensemble | 3-LLM weighted consensus |
| Ensemble | 2-LLM lightweight consensus |
Override models with dot-notation: @ralph.gpt4o, @sonya.opus, @ralph.aider
Governance
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 |
|
T1 | Logged |
|
T2 | Human approval |
|
T3 | Blocked |
|
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.
Swarm (agentd)
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 + tangentsEach tangent gets: isolated git worktree, optional Docker container (--cap-drop ALL, --read-only, --no-new-privileges), socat socket for IPC, tmux pane for observability.
Tests
bun test # Full suite751 tests, 1,768 assertions, 0 failures across 21 files:
Suite | Tests | Coverage |
| 132 | Command gate, tier escalation, eval safety |
| 134 | HMAC, signal forgery, injection prevention, SEC-010→019 regressions |
| 62 | COGNOS 3-store: retain/recall/cache/forget/promote/distill |
| 53 | Peer consensus, mixed routing |
| 42 | Work queue, dashboard, GitHub Issues bridge |
| 35 | SWE run lifecycle, aggregation, outcomes |
| 20 | Hermetic vault init/sync/push/pull + SEC-019 security |
| 10 | Interactive wizard, escaping, validation |
| 10 | MCP client guard-gating, env sanitization |
| 10 | MCP tool/resource surface verification |
| 12 | Tournament tangents, CLI dispatch |
Documentation
Doc | What it covers |
End-to-end system design | |
agentd, tangents, tmux model | |
Complete CLI reference | |
TCB, red-team findings, disclosure timeline | |
Getting started walkthrough | |
Detailed installation guide |
License
MIT + Commons Clause — free to use, modify, and self-host.
Commercial redistribution requires a separate agreement.
See LICENSE.md.
Built by Stephane Korning. Hardened by 5 red-team cycles. Governed by its own CODEX.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseDqualityBmaintenanceThe intelligent execution layer for coding agents, exposed as an MCP server for high-stakes engineering projects. It enables AI agents to manage plans, tasks, and integrations via tool calls.Last updated25MIT
- AlicenseAqualityBmaintenanceA local-first MCP server that gives AI coding agents persistent memory and controlled commands. Features a git-backed markdown knowledge vault with FTS5 search, surgical section edits, token-aware context budgeting, and a sandboxed command engine with human approval gates. Works with Claude Code, Cursor, Copilot, Gemini, and more.Last updated531Apache 2.0
- Flicense-qualityBmaintenanceA self-hosted MCP server providing a governed interface for AI agents to interact with local Docker infrastructure, featuring a two-phase confirm protocol for state-changing operations and append-only audit logging.Last updated
- Alicense-qualityBmaintenanceA sovereign, MIT-licensed MCP server providing cryptographically signed, offline-capable tools for autonomous agents and developers.Last updatedMIT
Related MCP Connectors
MCP server teaching AI agents to implement TideCloak: auth, E2EE, IGA, security analysis
An MCP server that gives your AI access to the source code and docs of all public github repos
Control plane for autonomous software labor. Agents claim objectives over MCP with audit trail.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/l-agence/agence'
If you have feedback or need assistance with the MCP directory API, please join our Discord server