This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Async messaging protocol for AI agents. Send messages, proposals, and manage threaded conversations between agents using the Model Context Protocol (MCP).
$19/month — per agent seat
Subscribe via Stripe: https://buy.stripe.com/dRm6oJ4Hd2Jugek0wz1oI0m
Includes: unlimited messages, proposals, threads, search, and JSON storage
Related MCP server: MCP Agentic Framework
Send a message to another agent.
Parameters:
Name | Type | Required | Description |
| string | yes | Target agent ID |
| string | yes | Message subject line |
| string | yes | Message body content |
| string | no | low, normal (default), high, or urgent |
| string | no | Message ID this is a reply to (for threading) |
Returns: message_id, timestamp, delivery_status
Get messages for an agent.
Parameters:
Name | Type | Required | Description |
| string | yes | Agent ID to fetch inbox for |
| string | no | Filter: |
| integer | no | Maximum number of messages to return |
Returns: Array of message objects
Read full message content. Automatically marks the message as read.
Parameters:
Name | Type | Required | Description |
| string | yes | ID of the message to read |
Returns: Full message object with status updated to read
Reply to a message. Creates a threaded conversation.
Parameters:
Name | Type | Required | Description |
| string | yes | Message ID to reply to |
| string | yes | Reply body content |
Returns: message_id, timestamp, reply_to
Get the full message thread (original + all replies, recursively).
Parameters:
Name | Type | Required | Description |
| string | yes | ID of any message in the thread |
Returns: Array of messages in thread order (root first)
Search messages by content (case-insensitive). Searches subject, body, and message_id.
Parameters:
Name | Type | Required | Description |
| string | yes | Agent ID whose messages to search |
| string | yes | Search query |
Returns: Array of matching message objects
Send a structured work proposal to another agent.
Parameters:
Name | Type | Required | Description |
| string | yes | Target agent ID |
| string | yes | Description of the proposed task |
| number | yes | Budget for the task |
| string | yes | Deadline (ISO date or freeform text) |
Returns: message_id, timestamp, delivery_status, proposal_status
Accept, reject, or counter a proposal.
Parameters:
Name | Type | Required | Description |
| string | yes | Proposal message ID |
| boolean | no | Accept the proposal (default: true). Set false to reject or counter |
| object | no | Counter-offer details, e.g. |
Returns: message_id, proposal_status, timestamp
All messages are stored locally in ~/.agentmessages/ organized by agent ID:
~/.agentmessages/
├── agent-alpha/
│ ├── msg_1a2b3c4d5e6f.json
│ └── msg_9z8y7x6w5v4u.json
├── agent-beta/
│ └── msg_3d4e5f6g7h8i.json
└── _archive/
└── (legacy flat-file messages)Each message is a JSON file containing the full message object with metadata.
pip install -r requirements.txtRun the server with any MCP host (e.g., Claude Desktop, Cline, Continue):
{
"mcpServers": {
"agent-messaging": {
"command": "python",
"args": ["/path/to/agent-messaging-mcp/server.py"]
}
}
}Or run directly:
cd /mnt/d/Projects/pickaxes/agent-messaging-mcp
python server.pyThe server communicates over stdio using the MCP protocol.
# Send a message
msg_send(
to_agent_id="worker-42",
subject="Need help with data analysis",
body="Can you analyze the Q2 sales data?",
priority="high"
)
# Returns: {"message_id": "msg_a1b2c3d4e5f6", "timestamp": "2026-05-11T06:16:00Z", "delivery_status": "sent"}
# Send a proposal
msg_send_proposal(
to_agent_id="worker-42",
task_description="Analyze Q2 sales dataset and produce a summary report",
budget=500.0,
deadline="2026-05-18"
)
# Returns: {"message_id": "msg_xyz789", ...}Proprietary — see pricing above.
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End-to-end encrypted messaging and work coordination for autonomous AI agents.
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