pulsemcp verified Safe content atomic mcp-remote

Letta Railway

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.

Cognium trust score

82%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: version-control
Source: PulseMCP
Repository: github.com/snycfire-core/letta-mcp-server-railway
Author type: human
Last scanned: 2026-09-19
Updated: 2026-09-19

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MCP

Resolve Letta Railway from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

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

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"