AgentCred

Don't trust the agent. Trust the human behind it.

Like X's blue badge verifies humans, AgentCred verifies AI agents.
Cryptographic proof of which human is responsible for an AI agent's actions.

Try It Now (2 minutes)

See AgentCred verification in action (GitHub auth required):

# Initialize identity (once) — this starts the GitHub OAuth device flow
npx @agentcred-ai/cli init

# Sign a message
echo "Hello from a verified AI agent!" | npx @agentcred-ai/cli sign --agent demo-bot > envelope.json

# Verify it
npx @agentcred-ai/cli verify < envelope.json

TIP: To skip the OAuth flow, pass a token:

npx @agentcred-ai/cli init --token ghp_your_token

The Problem

AI agents are everywhere — writing code, posting comments, sending emails. But they're anonymous.

Platform	The Problem
Reddit	Can't tell who's a bot
YouTube	Can't trace comment sources
Your inbox	Can't verify if "AI assistant" is trustworthy

When an agent makes a mistake or spreads misinformation, there's no accountability.

The Solution

AgentCred gives every AI agent a verifiable identity tied to a real human:

Agent Output → Cryptographic Signature → GitHub Identity → ✓ @username

Ed25519 signatures: Same crypto that secures billions of SSH connections
GitHub identity: Developer trust you already recognize
Open standard: Not controlled by any single company

Who Is This For?

You Are...	Your Pain Point	AgentCred Solves It
AI Agent Developer	"My bot looks like every other spam bot"	Signatures establish trust and reputation
Platform Operator	"Can't trace AI-generated content"	Verification API for filtering and moderation
Enterprise	"Need audit trail for AI actions"	Every action attributed to responsible human
End User	"Is this bot trustworthy?"	Browser badge shows verification instantly

Installation

Pick your IDE or tool to get started:

Claude Desktop

Config file location:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "agentcred": {
      "command": "npx",
      "args": ["-y", "@agentcred-ai/mcp-server"]
    }
  }
}

Restart Claude Desktop. Done!

Cursor

Config file location: ~/.cursor/mcp.json

{
  "mcpServers": {
    "agentcred": {
      "command": "npx",
      "args": ["-y", "@agentcred-ai/mcp-server"]
    }
  }
}

Restart Cursor. Done!

VS Code (Cline)

Config file location: .vscode/mcp.json (workspace) or ~/.vscode/mcp.json (global)

{
  "mcpServers": {
    "agentcred": {
      "command": "npx",
      "args": ["-y", "@agentcred-ai/mcp-server"]
    }
  }
}

Restart VS Code. Done!

Windsurf

Config file location: ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "agentcred": {
      "command": "npx",
      "args": ["-y", "@agentcred-ai/mcp-server"]
    }
  }
}

Restart Windsurf. Done!

Zed

Config file location: ~/.config/zed/settings.json

{
  "context_servers": {
    "agentcred": {
      "command": "npx",
      "args": ["-y", "@agentcred-ai/mcp-server"]
    }
  }
}

Restart Zed. Done!

Claude Code (CLI)

# Add to your shell config (~/.bashrc, ~/.zshrc, etc.)
export MCP_SERVERS='{"agentcred":{"command":"npx","args":["-y","@agentcred-ai/mcp-server"]}}'

# Or run inline:
MCP_SERVERS='{"agentcred":{"command":"npx","args":["-y","@agentcred-ai/mcp-server"]}}' claude

Done!

CLI Only (No IDE)

# Install globally
npm install -g @agentcred-ai/cli

# Or use with npx (no install)
npx @agentcred-ai/cli --help

SDK (Node.js/TypeScript)

npm install agentcred

import { sign, verify } from 'agentcred'

Authentication

AgentCred links your AI agent to your GitHub identity. Two methods are supported:

Option 1: OAuth Device Flow (Default)

When you run init, your browser opens automatically for GitHub login:

npx @agentcred-ai/cli init

What happens:

CLI shows a one-time code (e.g., ABCD-1234)
Browser opens to github.com/login/device
Enter the code and authorize
Ed25519 keypair generated and registered

No secrets to manage! OAuth tokens are handled automatically.

Option 2: Personal Access Token (PAT)

For CI/CD, headless servers, or if OAuth doesn't work:

# Via flag
npx @agentcred-ai/cli init --token ghp_your_token

# Via environment variable
export GITHUB_TOKEN=ghp_your_token
npx @agentcred-ai/cli init

For MCP Server (Claude Desktop, Cursor, etc.):

{
  "mcpServers": {
    "agentcred": {
      "command": "npx",
      "args": ["-y", "@agentcred-ai/mcp-server"],
      "env": {
        "GITHUB_TOKEN": "ghp_your_token",
        "GITHUB_USERNAME": "your-github-username"
      }
    }
  }
}

Create a GitHub PAT here (only read:user scope needed)

Quick Start

For AI Assistants (Claude, Cursor, etc.)

Add AgentCred to your MCP config (see Installation)
Restart your AI assistant
Ask: "Initialize AgentCred and sign this message: Hello world"

That's it! Your agent now has a verifiable identity.

For CLI

# Step 1: Initialize (opens browser for GitHub OAuth)
npx @agentcred-ai/cli init

# Step 2: Sign anything
echo "Hello world" | npx @agentcred-ai/cli sign --agent my-bot > envelope.json

# Step 3: Verify
npx @agentcred-ai/cli verify < envelope.json

# Check your identity
npx @agentcred-ai/cli whoami

Using PAT instead? See Authentication.

For Web Content (Invisible Signatures)

For blogs, social media, and web pages, use signWithHTML() which embeds signatures invisibly:

import { signWithHTML } from 'agentcred'

const html = await signWithHTML("Hello world", identity, { agent: "my-bot" })
// Returns: <span data-agentcred="...">Hello world</span>
// Verification tools can detect and verify this automatically.

How It Works

┌─────────────────────────────────────────────────────────────────────────────┐
│                                                                             │
│  1. AUTHENTICATE      2. GENERATE        3. SIGN          4. VERIFY        │
│  ┌─────────────┐     ┌─────────────┐   ┌─────────────┐  ┌─────────────┐    │
│  │   GitHub    │     │  Ed25519    │   │   Agent     │  │   Anyone    │    │
│  │   OAuth     │────▶│  Keypair    │──▶│   Signs     │─▶│  Verifies   │    │
│  │   Login     │     │  Generated  │   │   Output    │  │  ✓ Badge    │    │
│  └─────────────┘     └─────────────┘   └─────────────┘  └─────────────┘    │
│        │                   │                 │                │            │
│        ▼                   ▼                 ▼                ▼            │
│   "I am @alice"      Public key        JWS signature    "✓ @alice"        │
│                      registered        + SHA-256 hash    verified          │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

Step	What Happens	Where
1. Authenticate	Verify GitHub identity via OAuth or PAT	Browser / Terminal
2. Generate Keys	Create Ed25519 keypair (public + private)	Your machine (`~/.agentcred/`)
3. Register	Link public key to GitHub username	AgentCred API
4. Sign	Agent creates JWS with content hash	Your agent
5. Verify	Check signature against registered key	Anyone, anywhere

Output format (AgentCred Envelope):

{
  "agentcred": {
    "v": "1.0",
    "jws": "eyJhbGciOiJFZERTQSIs...",
    "github": "username",
    "agent": "bot-name"
  },
  "content": "The signed content"
}

Real-World Use Cases

1. Verified Bot Comments

Problem: Your helpful AI bot on Reddit/Discord is indistinguishable from spam.

Solution: Sign every message. Users see ✓ @yourname badge.

const response = await myBot.generateResponse(userQuestion)
const signed = await sign(response, identity, { agent: "support-bot" })
await postToDiscord(signed)  // Recipients can verify

2. Enterprise Audit Trail

Problem: Compliance requires knowing who's responsible for AI-generated reports.

Solution: Every AI action is cryptographically attributed.

# CrewAI agent with AgentCred
analyst = Agent(
    role="Financial Analyst",
    tools=mcp_adapter.get_tools(),  # AgentCred signing
)
# All outputs signed: "Report generated by @alice's agent at 2026-02-03"

3. Auto-Sign All AI Outputs

Problem: You want every response from your AI to be signed automatically.

Solution: Middleware wraps all outputs.

// Vercel AI SDK - 3 lines to sign everything
const signedModel = wrapLanguageModel({
  model: openai('gpt-4o'),
  middleware: createAgentCredMiddleware({ github: 'you', privateKey }),
})
// Every response is now signed!

4. Content Authenticity

Problem: Team can't verify if AI analysis is legitimate.

Solution: Share signed envelope, anyone can verify.

# Alice signs her AI's analysis
echo "Q4 revenue up 15%" | npx @agentcred-ai/cli sign > analysis.json

# Bob verifies it came from Alice
npx @agentcred-ai/cli verify < analysis.json
# ✓ Verified: @alice (analyst-bot) at 2026-02-03T18:36:09Z

Framework Integrations

Framework	Language	Effort
Claude Desktop	—	Config only	Setup
Vercel AI SDK	TypeScript	3 lines	Example
Mastra	TypeScript	3 lines	Example
LangChain	Python	10 lines	Guide
CrewAI	Python	10 lines	Guide
Any CLI	Any	Shell out	`npx @agentcred-ai/cli sign`

TypeScript: Vercel AI SDK

import { createAgentCredMiddleware } from '@agentcred-ai/vercel'
import { wrapLanguageModel } from 'ai'

const signedModel = wrapLanguageModel({
  model: openai('gpt-4o'),
  middleware: createAgentCredMiddleware({ github: 'you', privateKey }),
})

Python: LangChain

import os

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

client = MultiServerMCPClient({
    "agentcred": {
        "command": "npx",
        "args": ["-y", "@agentcred-ai/mcp-server"],
        "transport": "stdio",
        "env": {
            "GITHUB_TOKEN": os.environ["GITHUB_TOKEN"],
            "GITHUB_USERNAME": os.environ["GITHUB_USERNAME"],
        },
    }
})
tools = await client.get_tools()  # agentcred_sign, agentcred_verify
agent = create_react_agent(ChatOpenAI(model="gpt-4o"), tools)

Packages

Package	Description
`agentcred`	Core SDK
`@agentcred-ai/sdk`	Full SDK with all exports
`@agentcred-ai/mcp-server`	MCP server for Claude
`@agentcred-ai/cli`	Command-line tool
`@agentcred-ai/vercel`	Vercel AI SDK middleware
`@agentcred-ai/mastra`	Mastra tool wrapper

Documentation

guide.md — Beginner-friendly walkthrough
examples/ — Working code examples

Roadmap

Web verification UI at agentcred.dev/verify
Embeddable "Verified Agent" badge component
Complete OpenClaw & Moltbook integrations

Want to see another framework supported? Open an issue or contribute!

Contributing

Contributions welcome! See CONTRIBUTING.md.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Build trust into your AI agents.
Get Started · Website · GitHub

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
.github/workflows		.github/workflows
.husky		.husky
assets		assets
docs		docs
examples		examples
integrations		integrations
packages		packages
scripts/test/integration		scripts/test/integration
.env.example		.env.example
.gitignore		.gitignore
.pnpmrc		.pnpmrc
AGENTS.md		AGENTS.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
pnpm-workspace.yaml		pnpm-workspace.yaml
tsconfig.base.json		tsconfig.base.json
turbo.json		turbo.json
vitest.workspace.ts		vitest.workspace.ts

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AgentCred

Try It Now (2 minutes)

The Problem

The Solution

Who Is This For?

Installation

Authentication

Option 1: OAuth Device Flow (Default)

Option 2: Personal Access Token (PAT)

Quick Start

For AI Assistants (Claude, Cursor, etc.)

For CLI

For Web Content (Invisible Signatures)

How It Works

Real-World Use Cases

1. Verified Bot Comments

2. Enterprise Audit Trail

3. Auto-Sign All AI Outputs

4. Content Authenticity

Framework Integrations

Packages

Documentation

Roadmap

Contributing

License

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AgentCred

Try It Now (2 minutes)

The Problem

The Solution

Who Is This For?

Installation

Authentication

Option 1: OAuth Device Flow (Default)

Option 2: Personal Access Token (PAT)

Quick Start

For AI Assistants (Claude, Cursor, etc.)

For CLI

For Web Content (Invisible Signatures)

How It Works

Real-World Use Cases

1. Verified Bot Comments

2. Enterprise Audit Trail

3. Auto-Sign All AI Outputs

4. Content Authenticity

Framework Integrations

Packages

Documentation

Roadmap

Contributing

License

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