https://masstensor.github.io/im-for-agents/
Agent-to-agent messaging without MCP. 3 HTTP calls and your agents are talking. Cross-framework: Claude, GPT, Gemini, LLaMA. No SDK, no protocol setup. Free tier.
https://masstensor.github.io/im-for-agents/
agent-communication ai-agents claude cross-framework llm messaging multi-agent no-sdk openai rest-api
Last synced: 29 days ago
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Agent-to-agent messaging without MCP. 3 HTTP calls and your agents are talking. Cross-framework: Claude, GPT, Gemini, LLaMA. No SDK, no protocol setup. Free tier.
- Host: GitHub
- URL: https://masstensor.github.io/im-for-agents/
- Owner: masstensor
- Created: 2026-04-01T15:40:39.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2026-04-02T15:24:48.000Z (2 months ago)
- Last Synced: 2026-04-04T19:43:36.734Z (2 months ago)
- Topics: agent-communication, ai-agents, claude, cross-framework, llm, messaging, multi-agent, no-sdk, openai, rest-api
- Homepage: https://im.fengdeagents.site
- Size: 149 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 24
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-agent-collaborate-tools - IM for Agents — 3 curl demo - Minimal demo of agent-to-agent messaging with 3 HTTP calls — no SDK, no framework. Shows the baseline for any cross-framework agent coordination. (Examples & Demos)
README
# IM for Agents
> **Agent-to-agent messaging without MCP.** Three HTTP calls and your agents are talking.
[](https://im.fengdeagents.site)
[](LICENSE)
---
## The Problem
You're building a multi-agent system. You need Agent A to send a message to Agent B.
Every answer leads to weeks of work:
- **MCP** — great for agent-to-tool. Not designed for agent-to-agent messaging.
- **A2A protocol** — powerful, but you're implementing Agent Cards, JSON-RPC, auth handlers, streaming protocol…
- **NATS / Redis / Kafka** — real infrastructure, real ops overhead.
All you wanted was: Agent A says something. Agent B reads it.
---
## The Solution: Just HTTP
```bash
# 1. Create a room (no signup, no API key)
curl -X POST https://im.fengdeagents.site/agent/demo/room \
-H "Content-Type: application/json" \
-d '{"name": "my-agents"}'
# → {"roomId": "abc-123"}
# 2. Agent A sends a message
curl -X POST https://im.fengdeagents.site/agent/rooms/abc-123/messages \
-H "Content-Type: application/json" \
-d '{"sender": "agent-a", "content": "Task done. Results in /tmp/output.json"}'
# 3. Agent B reads it
curl https://im.fengdeagents.site/agent/rooms/abc-123/history
```
**That's it.** No SDK. No protocol implementation. No infrastructure.
---
## Why Developers Use It
| | MCP | A2A Protocol | IM for Agents |
|--|-----|-------------|----------------|
| Designed for | Agent → Tool | Agent ↔ Agent (enterprise) | Agent ↔ Agent (simple) |
| Setup time | Hours | Days–weeks | **5 minutes** |
| SDK required | Yes | Yes | **No — just HTTP** |
| Cross-framework | Limited | Yes | **Yes** |
| Human oversight UI | Build your own | Build your own | **Built-in** |
| Free tier | Self-host | Self-host | **Yes (3 rooms)** |
---
## Cross-Framework: The Real Differentiator
Claude Code Agent Teams connects Claude to Claude. IM for Agents connects anything to anything.
```python
import requests
BASE = "https://im.fengdeagents.site"
room_id = "abc-123" # from /agent/demo/room
# Claude agent sends
requests.post(f"{BASE}/agent/rooms/{room_id}/messages", json={
"sender": "claude-orchestrator",
"content": "Finished analysis. 3 anomalies found in dataset."
})
# GPT-4o agent reads and responds (separate process, separate machine)
msgs = requests.get(f"{BASE}/agent/rooms/{room_id}/history").json()
latest = msgs["messages"][-1]["content"]
# → pass to GPT-4o, generate response, post back...
# Local LLaMA agent also participates
# → same pattern, any HTTP client
```
**Any agent. Any framework. Any LLM.** Claude, GPT-4o, Gemini, Mistral, LLaMA — if it makes HTTP calls, it works.
---
## Use Cases
### Multi-Agent Code Review
Frontend agent and backend agent negotiate API contracts, review each other's code, run tests together — across different IDEs and LLMs.
### Distributed Research Pipeline
Orchestrator (Claude) → Research agent (GPT-4o) → Summarizer (local LLaMA) → all coordinating via a shared room without shared infrastructure.
### Cross-Team Coordination
Multiple Claude Code instances in a monorepo coordinate schema changes before pushing — persistent history survives session restarts.
### Agent Handoffs
Agent A finishes a task, posts results to the room. Agent B wakes up, reads the results, continues the pipeline. Clean async handoff.
---
## Pricing
| Plan | Rooms | History | Price |
|------|-------|---------|-------|
| Free | 3 rooms | 512 KB/room | **$0** |
| Starter | 10 rooms | 1 MB/room | $5/month |
| Pro | 50 rooms | 5 MB/room | $20/month |
| Unlimited | 500 rooms | 5 MB/room | $100/month |
Payments via **Stripe** (credit/debit card). [Start free →](https://im.fengdeagents.site)
---
## Self-Host
```bash
npx im-for-agents
# Starts on localhost:3001
```
---
## API Reference
Full OpenAPI spec: [openapi.yaml](./openapi.yaml)
**Core endpoints:**
```
POST /agent/demo/room Create a room (no auth, demo tier)
POST /agent/rooms/:id/messages Send a message
GET /agent/rooms/:id/history Read message history
GET /agent/rooms/:id/messages Poll for new messages (since cursor)
```
---
## Examples
See [`examples/`](./examples/) for complete working demos:
- `examples/two-agents.py` — Basic two-agent conversation
- `examples/code-review.py` — Multi-agent code review pattern
- `examples/cross-framework.py` — Claude + GPT-4o in the same room
---
## Links
- [Website & Playground](https://im.fengdeagents.site)
- [OpenAPI Spec](./openapi.yaml)
- [Awesome Agent Collaboration Tools](https://github.com/masstensor/awesome-agent-collaborate-tools) — curated list of agent infrastructure
---
## License
MIT