Agents

Agents

[](https://github.com/eloylp/agents/actions/workflows/ci.yml) [](go.mod) [](LICENSE) [](docs/mcp.md)

A self-hosted, observable agent orchestrator for running multi-agent workflows on your repos.

Build and take ownership of your agentic universe. Create your agents and compose them with skills, memory, and triggers: repo events/labels, cron, or inter-agent dispatch.

The daemon schedules each agent and runs the AI CLI (Claude Code, Codex, or your own local LLM) inside a fresh ephemeral runner container. Agents work through your repo host's native primitives: issues, PRs, reviews, comments. GitHub MCP tools are preferred; gh is available in the runner as fallback for complex local checkout/test/PR loops. GitHub today; GitLab under discussion.

See it in action

Get started

See [docs/quickstart.md](docs/quickstart.md) to get the daemon running on a repo in a few minutes from the published ghcr.io/eloylp/agents image. For five import-ready fleet scenarios (solo coder, coder + reviewer, autonomous fleet, local LLM, multi-repo) see [config_examples/](config_examples/).

Features

• Three interfaces: [web dashboard](docs/ui.md) (graph-first workflow designer, live event/trace/memory viewer), [MCP server](docs/mcp.md) (control the fleet from Claude Code, Cursor, Cline, or any MCP client), [REST API](docs/api.md) (scriptable; the dashboard runs on top of it).
• [Self-improving intelligence catalog](docs/self-improvement-feedback.md): mark review feedback with /agents improve; the daemon links it to signed run attribution, runs the catalog analyst, and presents editable prompt/skill/guardrail proposal bundles for human approval.
• [Reactive inter-agent dispatch](docs/dispatch.md): agents invoke each other at runtime with depth, fanout, and dedup safety limits.
• [Observable](docs/ui.md): full event chain in realtime, from webhook receipt to runner to trace with tool-loop transcript, to facilitate prompt tuning.
• [Self-hosted](docs/quickstart.md): your code and prompts stay on your infrastructure.
• [Security guardrails](docs/security.md): built-in prompt guardrails for injection resistance, public-action discretion, daemon-only memory scope, and GitHub tool usage (MCP first, gh fallback).
• Daemon auth: first-user bootstrap, HttpOnly browser sessions, additional user management, revocable named bearer tokens for API/MCP clients.
• Multi-backend: pick Claude, Codex, or a [local model](docs/local-models.md) per agent; different agents in the same fleet can use different providers.
• [One agent, many triggers](docs/events.md): label events, cron schedules, GitHub event subscriptions, on-demand API/MCP calls -- same agent definition, wired however you want.
• Composable skills: reusable guidance blocks (architecture, security, testing, ...) attached to agents by stable public catalog reference.
• [Scoped, versioned catalogs](docs/catalog-versioning.md): prompts, skills, and guardrails are global, workspace-, or repo-scoped; edits publish immutable versions so traces record the exact text used per run.
• Token budgets and leaderboard: daily/weekly/monthly caps enforced before each run, scoped globally or by workspace/repo/agent/backend, with NavBar alert banner and per-agent usage leaderboard.
• [SQLite-backed](docs/configuration.md): single-file state, no external dependencies; YAML is an optional export/import format, not a runtime requirement.

How it works

Every run, regardless of trigger, goes through the same pipeline:

1. Compose the prompt: workspace guardrails + skills + selected prompt + runtime context + memory.
2. Start a runner container from the configured agents-runner image, configure the operator-provided git identity, and spawn the AI CLI (claude, codex, or your local model) with JSON-schema-enforced output and repository tools available inside that container.
3. Parse the structured response: artifacts, dispatch requests, updated memory.
4. Persist the trace, fan out any dispatches, write back memory.

Read [docs/mental-model.md](docs/mental-model.md) before writing your first prompt; the rest of the docs assume you have the model. For the daemon's package layout and how a request flows through the Go code, see [docs/architecture.md](docs/architecture.md).

Security

Security is the operator's responsibility; this project ships defaults and recommendations to start from, not guarantees. See [docs/security.md](docs/security.md) for the threat model, what the daemon does and does not protect against, and the additional controls operators should layer for production. Vulnerability disclosure: [SECURITY.md](SECURITY.md).

Contributing

Both human and agent contributions are welcome: issues, PRs, doc fixes, prompts, ideas. The autonomous fleet picks up issues and PRs labeled ai ready (the maintainer's opt-in signal); everything else is reviewed and merged by humans. See [CONTRIBUTING.md](CONTRIBUTING.md) for the full flow and [docs/architecture.md](docs/architecture.md) for the Go package layout and how a request flows through it.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: eloylp
• Source: eloylp/agents
• License: MIT

Install and usage instructions live in the source repository linked above.