api
無料Use liter-llm api reference documentation.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llm2632026年10月26日 更新
無料GitHub で公開
liter-llm-using-the-mcp-server
Use when calling LLM APIs through the liter-llm MCP server's 22 tools, and to decide when MCP beats the CLI or SDK. Covers the tool surface, the auto-installing launcher, and authentication.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llmスター 263(GitHub 263 + cccskills 0)
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インストール方法を見る含まれるファイル（2）
- SKILL.md3.7 KB
- index.md483 B
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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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.
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同じリポジトリのスキル
cli
無料Use liter-llm cli reference documentation.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llm2632026年10月26日 更新
Universal LLM API client for 174 providers with native bindings for 14 languages. Use when writing code that calls LLM APIs via liter-llm in Python, TypeScript, Rust, Go, Java, C#, Ruby, PHP, Elixir, WASM, or C, when running the OpenAI-compatible proxy, or when calling LLMs through the MCP server. Covers chat, streaming, tool calling, embeddings, image generation, speech, transcription, moderation, web search, OCR, reranking, provider routing, middleware, and configuration.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llm2632026年10月26日 更新
Use when sending chat completions through liter-llm and routing to a specific provider via the `provider/model` prefix. Covers the chat call shape, provider routing, model_hint, message roles, and error categories.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llm2632026年10月26日 更新
Use when generating embeddings, calling the 12 web-search providers, or running OCR over documents with the 4 OCR providers through liter-llm. Covers embed, search, and ocr methods plus reranking.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llm2632026年10月26日 更新
Use when running the `liter-llm api` OpenAI-compatible gateway — virtual keys, per-key rate limits, budgets, cost tracking, and model routing. Covers the TOML config and the 22 REST endpoints.
日本語の概要は準備中です。原文の説明を表示しています。
xberg-io/liter-llm2632026年10月26日 更新