# Letta Railway

> Use this tool when you need to integrate stateful AI conversations into your workflow, enabling seamless interactions between AI clients and Letta.ai agents through HTTP transport. It solves problems of conversation history management and provides comprehensive agent lifecycle management, memory block operations, and conversation export functionality. Ideal for teams using MCP-compatible clients like Claude Desktop or GitHub Copilot, Letta Railway accepts client requests and outputs stateful conversation responses, making it suitable for applications requiring persistent context storage and robust error handling.

Canonical page: https://skillsregistry.net/skills/letta-railway  
JSON: https://api.skillsregistry.net/v1/skills/letta-railway

## Description

This Railway-deployable MCP server implementation by SNYCFIRE-CORE bridges AI clients with Letta.ai agents through HTTP transport, enabling stateful conversations without requiring clients to manage conversation history. Built with FastMCP and Python, it provides comprehensive agent lifecycle management (creation, configuration, deletion), memory block operations for persistent context storage, tool attachment/detachment capabilities, and conversation export functionality. The implementation includes robust error handling, retry logic, streaming support, and Railway-specific deployment configurations, making it particularly useful for teams wanting to integrate Letta's stateful AI agents into existing workflows through any MCP-compatible client like Claude Desktop, GitHub Copilot, or Cursor while maintaining persistent agent memory across sessions.

## Trust

- **Trust score (0–1):** 0.82
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/letta-railway)
- **Repository:** <https://github.com/snycfire-core/letta-mcp-server-railway>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "letta-railway"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/letta-railway` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/letta-railway/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt