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MCP server · Developer Tools

Agent Forge

Dispatch AI coding agents (Claude Code, Copilot, OpenCode) as MCP tools

Unclaimed MIT last commit 6 months ago devtools
39Low

Scored 8 days ago · breakdown

About Agent Forge

Agent Forge is an MCP server published by Cloud-Eye-Prime in the Developer Tools category: dispatch AI coding agents (Claude Code, Copilot, OpenCode) as MCP tools.

The repository has 24 stars and 2 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/Cloud-Eye-Prime/mcp-agent-forge

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Ask AI about Agent Forge

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I know everything about Agent Forge. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

Static checks derived from the repository 6 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
  • !Dependencies pinnedNo lockfile. Installs can pull different code over time.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.

1 check has not been run yet.

README

MCP Agent Forge

Dispatch AI coding agents as MCP tools. Fan out work to Claude Code, GitHub Copilot, and OpenCode from any MCP client -- Claude Desktop, your own orchestrator, or anything that speaks MCP.

Includes Bounded Plan safety -- constrain what agents can touch before they execute.

You (MCP Client)
    |
    |-- forge_plan("add error handling", no_touch=["auth.py", ".env"])
    |       -> preview: "Agent will touch 3 files, protect 2"
    |
    |-- forge_dispatch_plan("claude_code", "add error handling", ...)
    |       -> job_id: "forge-a1b2c3d4" (bounded execution)
    |
    |-- forge_status("forge-a1b2c3d4")
            -> status: "complete", bounded: true

Why?

You're already talking to Claude Desktop (or another MCP host). You want to delegate coding tasks to specialized agents without leaving your conversation. Agent Forge gives your orchestrator hands -- and Bounded Plans make sure those hands don't break things.

  • Claude Code -- Agentic, multi-file, reads CLAUDE.md. Best for complex tasks. ~$0.01-0.40/task.
  • GitHub Copilot CLI -- Free with GitHub Pro. Great for structured analysis and read-only work.
  • OpenCode -- Gemini Flash via OpenRouter. ~$0.003/task. Fast and cheap.

Install

# Clone
git clone https://github.com/Cloud-Eye-Prime/mcp-agent-forge.git
cd mcp-agent-forge

# Install dependency
pip install fastmcp

# Verify agents are available
claude --version        # Claude Code
github-copilot-cli      # Copilot (optional)
opencode --version      # OpenCode (optional)

You need at least one agent installed. Claude Code is the primary.

Install Claude Code

npm install -g @anthropic-ai/claude-code

Install OpenCode (optional)

npm install -g opencode

Configure with Claude Desktop

Add to your Claude Desktop MCP config (claude_desktop_config.json):

{
  "mcpServers": {
    "agent-forge": {
      "command": "python",
      "args": ["/absolute/path/to/mcp-agent-forge/server.py"],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-...",
        "OPENROUTER_API_KEY": "sk-or-..."
      }
    }
  }
}

Restart Claude Desktop. You now have seven tools available.

Tools

Core Dispatch

Tool Description
forge_dispatch Fire-and-forget dispatch. Returns job_id instantly.
forge_run Synchronous dispatch -- waits for result. Use for quick tasks.
forge_status Poll a running job for status and output.
forge_list List all jobs with their current status.

Bounded Plan (Safety)

Tool Description
forge_plan Preview a constrained execution plan before dispatching.
forge_dispatch_plan Dispatch with boundaries -- file limits, no-touch patterns, verification.

Bounded Plans

The most dangerous thing about AI coding agents is giving them unbounded access. "Refactor the auth module" sounds simple -- until the agent rewrites your database schema, deletes your tests, and installs three new dependencies.

Bounded Plans solve this. Before the agent executes, you define:

  • allowed_paths -- which files the agent may touch
  • no_touch -- which files are protected (auth, config, .env)
  • max_files -- hard cap on how many files can change
  • verification -- checks to run after execution
  • ground_rules -- additional constraints in plain language

The agent receives a rewritten prompt that includes all constraints. It doesn't see "refactor the auth module" -- it sees "refactor the auth module, but ONLY touch these 3 files, NEVER touch auth.py or .env, and verify with py_compile when done."

Example: Safe Refactoring

# Step 1: Preview the plan
forge_plan(
    task="Add error handling to all API route handlers",
    cwd="/home/me/myapp",
    max_files=4,
    allowed_paths=["src/routes/*.py", "src/middleware.py"],
    no_touch=["src/auth.py", "src/database.py", ".env", "migrations/"],
    verification=[
        "python -m py_compile src/routes/users.py",
        "python -m py_compile src/routes/orders.py",
        "python -m pytest tests/ -x --tb=short"
    ]
)

# Step 2: Review the constrained prompt, then execute
forge_dispatch_plan(
    agent="claude_code",
    task="Add error handling to all API route handlers",
    cwd="/home/me/myapp",
    max_files=4,
    allowed_paths=["src/routes/*.py", "src/middleware.py"],
    no_touch=["src/auth.py", "src/database.py", ".env", "migrations/"],
    verification=[
        "python -m py_compile src/routes/users.py",
        "python -m py_compile src/routes/orders.py",
        "python -m pytest tests/ -x --tb=short"
    ]
)

Default Ground Rules

Every bounded plan automatically includes these constraints:

  1. Do not modify any file not listed in allowed_paths
  2. Do not delete files unless explicitly asked
  3. Do not install new dependencies without mentioning it
  4. Verify your changes compile/parse before finishing
  5. If uncertain, explain what you would do instead of doing it

You can add more with the ground_rules parameter.

Usage Patterns

Pattern 1: Simple dispatch (unbounded)

For low-risk tasks where you trust the agent:

forge_dispatch("claude_code", "fix the typo in README.md", "/myapp")

Pattern 2: Bounded dispatch (safe)

For anything touching production code:

forge_dispatch_plan(
    agent="claude_code",
    task="optimize the database query in user_service.py",
    cwd="/myapp",
    max_files=1,
    allowed_paths=["src/services/user_service.py"],
    no_touch=["src/models/", "src/auth/", "alembic/"],
    verification=["python -m py_compile src/services/user_service.py"]
)

Pattern 3: Fan-out

Dispatch multiple agents on different tasks simultaneously:

forge_dispatch("claude_code", "refactor auth to use JWT", "/myapp")
forge_dispatch("opencode", "add type hints to utils.py", "/myapp")
forge_dispatch("copilot", "explain the database schema", "/myapp")

Poll all three. Collect results. Synthesize.

Pattern 4: Research then execute

# Step 1: cheap read with OpenCode
forge_run("opencode", "list all files that import auth_middleware", "/myapp")

# Step 2: bounded execution with Claude Code
forge_dispatch_plan(
    agent="claude_code",
    task="update auth_middleware imports to use new pattern from utils.py",
    cwd="/myapp",
    max_files=3,
    no_touch=["src/auth_middleware.py"],
    verification=["python -m py_compile src/routes/api.py"]
)

Pattern 5: Agent comparison

Send the same task to multiple agents and compare:

forge_dispatch("claude_code", "review this PR for security issues", "/myapp")
forge_dispatch("opencode", "review this PR for security issues", "/myapp")

Different models catch different things.

Agent Comparison

Agent Model Cost Speed Writes Files? Best For
claude_code Sonnet 4.6 $0.01-0.40 15-135s Yes Complex multi-file changes, agentic tasks
copilot Sonnet 4.6 (via GitHub) Free 30-60s Limited Analysis, structured reports, Q&A
opencode Gemini Flash ~$0.003 14-25s Yes Fast reads, simple rewrites, type hints

Tips

  • Always pass absolute paths for cwd. Relative paths resolve from the server's working directory.
  • Use Bounded Plans for production code. Unbounded dispatch is fine for exploration and analysis. Use forge_dispatch_plan when changes matter.
  • Poll every 10-30 seconds for long tasks. Claude Code can take up to 5 minutes.
  • Claude Code reads CLAUDE.md -- if your project has one, the agent follows those conventions.
  • Copilot may not write files in headless mode. Use it for analysis, not execution.
  • The no_touch list is your safety net. Always protect auth, config, env files, and database migrations.

Cloud-Eye LXR-5 (Optional Cloud Brain)

Agent Forge gives your orchestrator hands. Cloud-Eye LXR-5 gives it a brain -- persistent memory, workspace isolation, 20-tool agent loops, thermodynamic routing, and institutional knowledge that accumulates across sessions.

If you outgrow stateless agent dispatch and want agents that remember, learn, and coordinate -- check out Cloud-Eye.

License

MIT. Use it, fork it, build on it.


Built by Cloud-Eye Prime -- the Dragon's open hand.

README fetched from the repository 6 days ago. The original is authoritative.

Questions

About Agent Forge

How do I install Agent Forge?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Agent Forge safe to use with an AI agent?

Its trust score is 39 out of 100 (low). It passes 3 of the 5 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Agent Forge still maintained?

The last commit was 6 months ago and 1 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.