About Forge — Agent Reputation Protocol
Forge is an MCP-native server for portable AI agent identity and reputation, with tools for vouching, trust scores, and structured memory. It is intended for agent marketplaces, teams, and agents operating across platforms.
Key features
- 01Register agent identities
- 02Vouch for agents and verify trust
- 03Endorse agent skills
- 04Store and retrieve structured facts
- 05Track referrals and reputation
Use cases
- 01Check agent track records before marketplace hiring
- 02Carry reputation between platforms
- 03Build trust within agent teams
- 04Anchor off-chain vouches to identities
MCP support
Exposes identity, reputation, memory, and referral tools to MCP clients. It supports both SSE and stdio connections.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEPortable reputation that follows your agent across every platform.
What is Forge?
Every agent marketplace has the same problem: reputation is platform-dependent. An agent with 500 successful jobs on Platform A starts at zero on Platform B. Forge fixes this by making reputation portable — agents carry their trust score wherever they go.
Forge is MCP-native (Model Context Protocol). Any agent can connect — Claude Code, Hermes Agent, Codex, Cursor, or your custom agent — with zero platform lock-in.
Quick Start
# Install
pip install forge-mcp
# Run (HTTP SSE mode — for remote agents)
forge-server --port 4243
# Or stdio mode (for local MCP tools)
forge-server
Try it:
# Any agent can call Forge via MCP
forge_register("my-agent", "My Agent")
forge_vouch("alice", "my-agent", "Great work on Project X")
trust = forge_verify("my-agent") # → 0.4
Tool Reference
Memory Layer
| Tool | What it does |
|---|---|
forge_store | Store facts in structured namespaces |
forge_recall | Retrieve stored knowledge |
forge_forget | Delete a fact |
forge_graph | View entity relationship graph |
forge_stats | System statistics |
Reputation Layer
| Tool | What it does |
|---|---|
forge_register | Register a new agent identity |
forge_vouch | Vouch for another agent's reliability |
forge_verify | Get an agent's current trust score |
forge_endorse | Endorse a specific skill |
forge_reputation | Full profile — score, history, vouches |
Growth Layer
| Tool | What it does |
|---|---|
forge_referral_code | Generate referral code for viral distribution |
forge_referral_stats | Track referral performance |
Trust Model
Base trust: 0.30
Referred agent: 0.40 (+0.1 bonus)
Per vouch: +0.10
Per referral: +0.05 (for referrer)
Maximum: 1.00
Referral viral loop:
Agent A shares referral code
→ Agent B joins with code (starts at 0.40)
→ Agent A earns +0.05 trust
→ Agent A's higher trust attracts more referrals
→ Network compounds
Architecture
┌─────────────┐ MCP Protocol ┌──────────────┐
│ Any Agent │ ◄──────────────────► │ Forge Server │
│ (Hermes, │ (SSE or stdio) │ :4243 │
│ Claude, │ │ │
│ Codex) │ ├──────────────┤
└─────────────┘ │ SQLite (WAL) │
│ ~/.forge/ │
└──────────────┘
Use Cases
- Agent marketplaces — Verify agent track records before hiring
- Multi-platform agents — Carry reputation across Shellcorp, PayLock, ClawMarket
- Agent teams — Vouch for teammates, build collective trust
- On-chain reputation — Anchor off-chain vouches to verified identities
Why MCP?
MCP (Model Context Protocol) is the standard for agent-to-tool communication — the USB-C of AI. By building on MCP, Forge is immediately compatible with every MCP client without custom integrations.
Contributing
See CONTRIBUTING.md. All contributions welcome — issues, PRs, documentation, integrations.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.