<!-- AI-RULEZ :: GENERATED FILE — DO NOT EDIT Content-Hash: blake3:6925dd58f9790a1cc57f093167cf3b430886393ff3792d28003f15269b5546a2 Source-Hash: blake3:e9a3504d653cf1d11dce92e35c7dc252403c7cac2ca0cae3c0b8c8addd45159e Schema-Version: v1 -->

Using the MCP Server

The liter-llm MCP server exposes 22 tools that mirror the proxy's REST endpoints, so an MCP-compatible client (Claude Code, Claude Desktop) can call 174 LLM providers as tools with no glue code.

Standalone skill installation

Installing this skill alone does not register an MCP server or include the plugin launcher. Install the CLI (for example, brew install xberg-io/tap/liter-llm), then configure your MCP client with liter-llm mcp --transport stdio as its stdio command. The full product plugin supplies registration where the runtime supports MCP.

How it runs in this plugin

The plugin auto-registers the server. Its command is the bundled launcher scripts/mcp-launch.sh, which execs liter-llm mcp --transport stdio. On first run the launcher resolves a liter-llm binary: it reuses one on PATH, then tries npx/uvx, then Homebrew, then downloads a prebuilt from the tool's latest GitHub release. Override with LITER_LLM_LAUNCHER=auto|npx|uvx|brew|download.

To run it manually:

liter-llm mcp --transport stdio          # for Claude Code / Claude Desktop
liter-llm mcp --transport http --port 3001

Configure model routing

Provider-backed tools use the proxy model registry. Create liter-llm-proxy.toml in the working directory, or pass --config /absolute/path/liter-llm-proxy.toml when launching:

[[models]]
name = "gpt-4o"
provider_model = "openai/gpt-4o"

Supply OPENAI_API_KEY in the MCP process environment, then call chat using the configured name gpt-4o. list_models shows configured names; an unknown model is a request error. Missing credentials are also reported on provider-backed requests. Gemini filters host credentials: install with --skip-settings and configure the selected provider through gemini extensions config liter-llm "OpenAI key". Local stdio does not need a separate proxy virtual key.

The 22 tools

Modality tools: chat, embed, generate_image, speech, transcribe, moderate, rerank, search, ocr.

Model listing: list_models.

File operations: create_file, list_files, retrieve_file, delete_file, file_content.

Batch operations: create_batch, list_batches, retrieve_batch, cancel_batch.

Responses API: create_response, retrieve_response, cancel_response.

Authentication

Local stdio trusts the invoking local client by default, so the registered command starts without extra proxy authentication configuration. Provider API keys still come from environment variables and are needed for provider-backed requests.

To apply a restricted virtual key, configure mcp.stdio_key_id; an unknown key fails startup. Set mcp.stdio_trust_local = false to require an explicit virtual key. HTTP transport retains its authentication policy; the local stdio default does not disable HTTP authorization.

When to prefer MCP over the CLI or SDK

• Prefer MCP inside an agent session: the agent invokes tools directly, with no code to write or process to manage.
• Prefer the SDK when building application software in a specific language.
• Prefer the proxy when many apps or teams need a shared OpenAI-compatible endpoint with keys, budgets, and rate limits.