agent-graph-mcp 0.2.6

Run 9 agents at once — MCP server for graph-orchestrated LLM workflows with parallel fan-out (up to 16 nodes), checkpoint/resume, HITL approvals, HMAC receipts
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# agent-graph-mcp

**Run 9 agents at once.** MCP server for graph-orchestrated LLM workflows — dispatch up to 16 LLM nodes in parallel fan-out with typed joins, checkpoint/resume, human-in-the-loop approvals, and HMAC-authenticated execution receipts. 25 typed tools.

[![Crates.io](https://img.shields.io/crates/v/agent-graph-mcp)](https://crates.io/crates/agent-graph-mcp)
[![docs.rs](https://img.shields.io/docsrs/agent-graph-mcp)](https://docs.rs/agent-graph-mcp)
[![MCP Badge](https://lobehub.com/badge/mcp-full/recursiveintell-agent-graph-mcp?theme=light)](https://lobehub.com/mcp/recursiveintell-agent-graph-mcp)
[![npm](https://img.shields.io/npm/v/@recursiveintell/agent-graph-mcp)](https://www.npmjs.com/package/@recursiveintell/agent-graph-mcp)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE-MIT)

![Architecture](assets/architecture.svg)

> **Expose the `ri-agent-graph` runtime engine over MCP.** Compile declarative JSON workflow specs, execute synchronously or asynchronously, checkpoint/resume, request human approval, capture source witnesses, and get cryptographic receipts — all through 25 typed MCP tools. Normal execution is synchronous. Durable approval is supported only as a SQLite-backed decision.

## Quick start

### npx (recommended)

```bash
npx -y @recursiveintell/agent-graph-mcp --direct --base-url http://127.0.0.1:11434 --model glm-5.2:cloud
```

### Cargo install

```bash
cargo install agent-graph-mcp --locked
agent-graph-mcp --direct --base-url http://127.0.0.1:11434 --model glm-5.2:cloud
```

### Daemon mode (production)

```bash
agent-graph-mcpd --data-dir ~/.local/share/agent-graph --socket /tmp/agent-graph.sock &
agent-graph-mcp --socket /tmp/agent-graph.sock
```

## Client configs

**Hermes Agent:**
```yaml
mcp_servers:
  agent_graph:
    command: agent-graph-mcp
    args: [--socket, /tmp/agent-graph.sock]
```

**Claude Desktop:**
```json
{"mcpServers": {"agent-graph": {"command": "npx", "args": ["-y", "@recursiveintell/agent-graph-mcp", "--direct", "--base-url", "http://127.0.0.1:11434", "--model", "glm-5.2:cloud"]}}}
```

## 9 agents at once

Fan out to 9 LLM nodes in parallel, then join results into one synthesis:

```json
{
  "name": "9-agent-research-sweep",
  "entry": "fanout",
  "nodes": [
    {"id": "fanout", "type": "passthrough"},
    {"id": "agent_0", "type": "llm", "prompt": "Research topic A: {input}"},
    {"id": "agent_1", "type": "llm", "prompt": "Research topic B: {input}"},
    {"id": "agent_2", "type": "llm", "prompt": "Research topic C: {input}"},
    {"id": "agent_3", "type": "llm", "prompt": "Analyze dimension 1: {input}"},
    {"id": "agent_4", "type": "llm", "prompt": "Analyze dimension 2: {input}"},
    {"id": "agent_5", "type": "llm", "prompt": "Analyze dimension 3: {input}"},
    {"id": "agent_6", "type": "llm", "prompt": "Critique from angle X: {input}"},
    {"id": "agent_7", "type": "llm", "prompt": "Critique from angle Y: {input}"},
    {"id": "agent_8", "type": "llm", "prompt": "Synthesize findings: {collected}"},
    {"id": "join", "type": "join", "config": {"inputs": ["agent_0","agent_1","agent_2","agent_3","agent_4","agent_5","agent_6","agent_7","agent_8"], "output": "collected", "mode": "collect_array"}},
    {"id": "report", "type": "llm", "prompt": "Produce final report from: {collected}"}
  ],
  "edges": [
    {"from": "fanout", "to": "agent_0"}, {"from": "fanout", "to": "agent_1"},
    {"from": "fanout", "to": "agent_2"}, {"from": "fanout", "to": "agent_3"},
    {"from": "fanout", "to": "agent_4"}, {"from": "fanout", "to": "agent_5"},
    {"from": "fanout", "to": "agent_6"}, {"from": "fanout", "to": "agent_7"},
    {"from": "fanout", "to": "agent_8"},
    {"from": "agent_0", "to": "join"}, {"from": "agent_1", "to": "join"},
    {"from": "agent_2", "to": "join"}, {"from": "agent_3", "to": "join"},
    {"from": "agent_4", "to": "join"}, {"from": "agent_5", "to": "join"},
    {"from": "agent_6", "to": "join"}, {"from": "agent_7", "to": "join"},
    {"from": "agent_8", "to": "join"},
    {"from": "join", "to": "report"}, {"from": "report", "to": "END"}
  ],
  "max_parallelism": 9
}
```

All 9 LLM calls execute concurrently via Tokio `JoinSet`. The join node collects results, then the report node synthesizes. Scale up to 16 branches per parallel node.

## Architecture

```
MCP Client ──→ agent-graph-mcp (proxy) ──Unix socket──→ agent-graph-mcpd (daemon) ──→ SQLite
               stdin/stdout                 framed              Tokio async I/O
```

## Tools (25)

**Graph lifecycle (4):** `graph_create`, `graph_list`, `graph_inspect`, `graph_render`
**Execution (5):** `graph_execute`, `graph_run_start`, `graph_run_wait`, `graph_run_cancel`, `graph_run_get`
**State & checkpoint (4):** `graph_run_state`, `graph_run_events`, `graph_run_checkpoint`, `graph_run_resume`
**HITL approval (3):** `graph_approval_list`, `graph_approval_get`, `graph_approval_request`
**Evidence (2):** `graph_source_witness_capture`, `graph_source_witness_get`
**Templates (4):** `graph_template_list`, `graph_template_instantiate`, `graph_template_candidates`, `graph_template_outcomes`
**Receipts & status (3):** `graph_policy_check`, `graph_run_receipt`, `graph_status`

## Built-in templates

| Template | Description |
|----------|-------------|
| `council_deliberation` | 3-analyst parallel council |
| `parallel_council` | 2-person debate |
| `plan_critique_refine` | plan → critique → refine |
| `analysis_pipeline` | planner → researcher → extractor → synthesizer → validator |
| `classifier_router` | LLM classifier → bug/feature/question handlers |

## Ecosystem

| Crate | Role |
|-------|------|
| [agent-graph-mcp](https://crates.io/crates/agent-graph-mcp) | MCP server (this repo) |
| [ri-agent-graph](https://crates.io/crates/ri-agent-graph) | Core graph engine |
| [llm-pipeline](https://crates.io/crates/llm-pipeline) | LLM node payloads |
| [stack-ids](https://crates.io/crates/stack-ids) | Trace primitives |

## Verification

```bash
# Smoke test — 25 tools
echo '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}' | \
  npx -y @recursiveintell/agent-graph-mcp --direct --base-url http://127.0.0.1:11434 --model glm-5.2:cloud 2>/dev/null | \
  python3 -c "import sys,json; msg=json.loads(sys.stdin.read()); print(f'{len(msg[\"result\"][\"tools\"])} tools')"

# Build + test
cargo build --release
cargo test --lib --test daemon_recovery --test mcp_integration
```

## License

MIT © [RecursiveIntell](https://github.com/RecursiveIntell)