Signal MCP
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.
Signal MCP
Signal is a lightweight MCP work queue for AI agents.
It provides a small set of tools for creating, claiming, starting, handing off, failing, completing, and reviewing durable work items through MCP.
Signal is intentionally simple.
v0.1.0
The first release provides a basic agent work lifecycle:
created
↓
claimed
↓
in_progress
↓
completedWith additional paths for:
handoff
failedRelated MCP server: Agent Task List MCP Server
MCP Tools
Tool | Description |
| Check that Signal and SQLite are available |
| Create a new Signal work item |
| Retrieve a Signal by ID |
| List recent Signals |
| Assign a Signal to an agent |
| Mark a claimed Signal as in progress |
| Transfer a Signal to another agent |
| Mark a Signal as failed |
| Mark a Signal as completed |
Stack
TypeScript
Model Context Protocol
Streamable HTTP
SQLite
Docker
Docker Compose
Connect
Signal exposes an MCP endpoint at:
Run
cp .env.example .env
docker compose up -dBy default, Signal is exposed at:
http://localhost:3002/mcpThe container listens internally on port 3000.
Persistence
Signal stores work state in SQLite.
The Docker Compose setup mounts the database outside the container so work survives container replacement and restarts.
Status
v0.1.0 is intentionally small.
The goal of this release is to establish a simple, durable MCP work queue before adding more advanced features such as milestones, dependencies, events, artifacts, reviews, or workflow policies.
Those features will be shaped by actual agent usage rather than added in advance.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Related MCP Connectors
Project tracker for AI agents and teams: file, claim, update and hand off tickets over MCP.
Durable background job execution, async task scheduling, and state persistence for AI agents.
Persistent memory, knowledge graph, task management and more for AI agents via MCP.
MCP-first toolbox for agents: KV storage, auth, queue, and utility tools. Free in early access.
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