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PopNx MCPMCP servers for people who use AI · explained in plain words

Agence

by l-agenceversion 1.0.0i★ –iRuns on your computer
Registry nameio.github.l-agence/agence

Install

Overview

Description from the maker (original English)

AI governance MCP server — policy enforcement, skills, memory, multi-LLM consensus

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: AGENCE_ROOT

You need

  • npmNode.js installed (for the npx command)

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-agence

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

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.

Open in VS Code

Or copy the settings yourself

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.

Values you fill in

  • AGENCE_ROOT env
    Path to agence installation root (auto-detected if installed via npm)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account l-agence, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 5670 servers in this category
  • Published to the registry more recently than 12% of the other 5670 servers in this category
  • Basic checks equal to or better than 100% of the other 5670 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Agence safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 6 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 2 months ago
Install

README from the maker

Open the README

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.

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."*


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:

TierGateExample
T0Auto-executegit status, ls, cat
T1Loggedgit add, git commit
T2Human approval requiredgit push, git reset
T3Blockedrm -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.


By the Numbers

30,701Lines of production code (23.9K TypeScript + 6.8K bash)
751Tests with 1,768 assertions across 21 files
279Security-specific tests (guard + hardening + SEC regressions)
9Red-team cycles completed (SEC-008 through SEC-019)
33+Orchestration skills (^fix, ^review, ^hack, ^peers, ^vault...)
18Registered agents (10 persona, 5 tool, 1 loop, 2 ensemble)
12LLM providers (Anthropic, OpenAI, Azure, Google, Mistral, Groq, Ollama...)
10MCP tools + 3 MCP resources (Model Context Protocol server)
3Dependencies total (MCP SDK, Bun, Zod)
0Databases 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 }}"
InputDescriptionDefault
commandShell command to classifyrequired
policyPath to custom AIPOLICY.yaml (repo-relative)bundled policy
agentAgent identity for MLS capability checksci
fail_on_blockExit 1 on T3 (deny)true
fail_on_escalateExit 1 on T2 (requires approval)false
OutputValues
tierT0 · T1 · T2 · T3
actionallow · flag · escalate · deny
reasonHuman-readable decision
ruleMatched 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
ToolRequiredInstall
bash 4+YesBuilt-in on Linux/macOS/WSL
git 2.30+Yessudo apt install git
bun 1.3+Yesbun.sh
tmuxFor swarmsudo apt install tmux
jqFor ledger queriessudo apt install jq

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 --help


Architecture

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:

PillarPurposeLocation
CODEXImmutable governance — Laws, Principles, Rules, AIPOLICYcodex/
KNOWLEDGETeam-shared docs, lessons, plans — selectively routed via @ symlinksknowledge/
NEXUSLocal operational state — sessions, ledger, signalsnexus/ (gitignored)
ORGANICSwarm orchestration — tasks, workflows, matrix schedulingorganic/

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

PrefixModeExampleUse When
_(none)_Chatagence "explain this error"Advice, explanation, Q&A
^Knowledgeagence ^save, agence ^lessonShared state, knowledge ops
~Privateagence ~note "idea"Private notes (never committed)
+Autonomousagence +refactor-authAgent plans & executes a task
/Validatedagence /git-statusPre-approved safe commands
!Systemagence !ralph, agence !claudeLaunch agents or tools
@Routeagence @sonya "review this"Send to specific agent

Agent Roster

AgentTypeBest For
@ralphLoopAutonomous iteration with backpressure
@sonyaPersonaArchitecture, code review
@claudiaPersonaDeep reasoning, critical decisions
@chadPersonaDevOps, infra, CI/CD
@alephPersonaRed team, security analysis
@claudeToolClaude Code CLI (headless spawn)
@aiderToolCode patches, git diffs
@pilotToolGitHub Copilot CLI
@peersEnsemble3-LLM weighted consensus
@pairEnsemble2-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.

TierGateExample
T0Auto-executegit status, ls, cat
T1Loggedgit add, git commit
T2Human approvalgit push, git reset
T3Blockedrm -rf, chmod 777
T4NeverForce 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 + 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.


Tests

bun test                          # Full suite

751 tests, 1,768 assertions, 0 failures across 21 files:

SuiteTestsCoverage
guard.test.ts132Command gate, tier escalation, eval safety
security-hardening.test.ts134HMAC, signal forgery, injection prevention, SEC-010→019 regressions
memory.test.ts62COGNOS 3-store: retain/recall/cache/forget/promote/distill
peers-dispatch.test.ts53Peer consensus, mixed routing
queue.test.ts42Work queue, dashboard, GitHub Issues bridge
runs.test.ts35SWE run lifecycle, aggregation, outcomes
vault.test.ts20Hermetic vault init/sync/push/pull + SEC-019 security
setup.test.ts10Interactive wizard, escaping, validation

| mcp-client.test.ts

Only the beginning is shown; read the rest in the repo

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