A Model Context Protocol (MCP) server that provides structured workflows and tools for AI agents working with software development projects, with
A Model Context Protocol (MCP) server that provides structured workflows and tools for AI agents working with software development projects, with specialized focus
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Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| build_functional_requirements | Collects comprehensive project requirements |
| build_prd | Generates Product Requirements Documents from functional requirements |
| build_frd | Creates Feature Requirements Documents for specific features |
| build_tdd | Breaks down features into detailed implementation plans with commit-level subtasks |
| build_architecture | Generates comprehensive architecture documentation |
| initialize_task | Sets up implementation subtasks from TDD plans |
| execute_task | Executes individual tasks with review checkpoints |
{
"mcpServers": {
"Railagent": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"cestbalez/railagent:latest"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
Store entities, relations and observations in a local knowledge graph with the reference Memory MCP server.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
Chat with your second brain — search, read and write vault notes through the Local REST API.
Enables AI assistants to securely interact with Azure DevOps through a standardized protocol.