api
免费Use liter-llm api reference documentation.
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xberg-io/liter-llm2632026年10月26日 更新
免费在 GitHub 公开
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.
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xberg-io/liter-llm星标 263(GitHub 263 + cccskills 0)
集成工具OpenAI
实测评分 未实测
查看安装方法包含的文件（2）
- SKILL.md3.7 KB
- index.md483 B
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
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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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同一仓库的技能
cli
免费Use liter-llm cli reference documentation.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
xberg-io/liter-llm2632026年10月26日 更新