Mcp Llm Gateway
Route MCP tool calls through a single LLM gateway that proxies completion requests so agents share one inference configuration.
Overview
io.github.daedalus/mcp-llm-gateway is a MCP server for the Build phase that proxies LLM completion requests for MCP-compatible clients.
What is this MCP server?
- MCP-compatible gateway that proxies LLM completion requests
- PyPI package `mcp-llm-gateway` v0.1.0 with stdio transport
- Source repository: github.com/daedalus/mcp-llm-gateway
- Centralizes model routing for multiple agent sessions or tools
- Gateway MCP server—not a hosted model marketplace or prompt library
- PyPI package identifier: mcp-llm-gateway
- Published server version: 0.1.0
- Transport: stdio MCP
What problem does it solve?
Every MCP tool and agent profile repeats different LLM endpoints and keys, making local experiments brittle and hard to swap models.
Who is it for?
Indie builders standardizing LLM access across MCP workflows while prototyping agents, internal tools, or multi-step automations.
Skip if: Teams that need a fully managed enterprise gateway with billing dashboards and no self-hosted proxy setup.
What do I get? / Deliverables
One stdio MCP gateway can front your completion calls so agents share a consistent proxy configuration during Build and agent-tooling work.
- Stdio MCP server that proxies completion requests
- Shared LLM routing layer for multiple agent tools
- Configurable gateway bridge between MCP clients and your inference backend
Recommended MCP Servers
Journey fit
LLM gateways are wired while you assemble agent stacks, prompts, and tooling—core Build work for AI-native products and dev workflows. Agent-tooling is the canonical shelf because the server’s purpose is proxying completions for MCP-compatible clients, not shipping end-user launch copy.
How it compares
MCP LLM proxy server, not a prompt engineering skill or model benchmarking harness.
Common Questions / FAQ
Who is io.github.daedalus/mcp-llm-gateway for?
Developers building MCP-heavy agent setups who want a single gateway to proxy completion traffic instead of per-tool provider configs.
When should I use io.github.daedalus/mcp-llm-gateway?
During Build while you wire agent-tooling, test alternate models, or unify LLM routing before you ship customer-facing features.
How do I add io.github.daedalus/mcp-llm-gateway to my agent?
Install `mcp-llm-gateway` from PyPI, configure the gateway’s upstream LLM settings and API keys, then register it as a stdio MCP server in your client.