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Coala Client

coala-client是coala生态的CLI工具，核心功能包括与OpenAI兼容LLM、MCP服务器聊天，导入CWL工具集为MCP服务器，导入/加载技能，可选沙箱执行shell命令。典型场景：交互式对话、单次提问、MCP服务器管理（导入、列表、调用）、技能管理。通过命令行指令操作，输出对话内容、工具执行结果等，支持配置环境变量与自定义路径。

hubentu
hubentu
热度 41.80
最近更新 2026-05-14 12:26:09
分类：开发依赖：纯提示词应用场景：API 集成 / 概念解释 / DevOps

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add skills-4
Metadata
name
coala-client
description
How to use the coala-client CLI for chat with LLMs, MCP servers, and skills. Use when the user asks how to use coala, run coala chat, add MCP servers, import CWL toolsets, list or call MCP tools, import or load skills, or use the sandbox run_command tool.
homepage
https://github.com/coala-info/coala_client
metadata
{"clawdbot":{"emoji":"🧬","requires":{"bins":["coala-client"]},"install":[{"id":"uv","kind":"uv","package":"coala-client","bins":["coala-client"],"label":"Install coala-client (uv)"}]}}

Coala Client

Part of the coala ecosystem. CLI for chat with OpenAI-compatible LLMs (OpenAI, Gemini, Ollama) and MCP (Model Context Protocol) servers. Supports importing CWL toolsets as MCP servers, importing skills, and an optional sandbox to run shell commands.

Config paths

  • MCP config and toolsets: ~/.config/coala/mcps/
    • mcp_servers.json — server definitions
    • <toolset>/ — per-toolset dirs with run_mcp.py and CWL files
  • Skills: ~/.config/coala/skills/ (one subfolder per imported source)
  • Env: ~/.config/coala/env (optional; key=value for providers and MCP env)

Quick start

  1. Init (first time)
    coala init — creates ~/.config/coala/mcps/mcp_servers.json and env.

  2. Set API key
    e.g. export OPENAI_API_KEY=... or export GEMINI_API_KEY=.... Ollama needs no key.

  3. Chat
    coala or coala chat — interactive chat with MCP tools.
    coala ask "question" — single prompt with MCP.

  4. Options
    -p, --provider (openai|gemini|ollama|custom), -m, --model, --no-mcp, --sandbox.

MCP: CWL toolsets

No API key needed for MCP import, list, or call — only for chat/ask with an LLM.

  • Import (creates toolset under ~/.config/coala/mcps/<TOOLSET>/ and registers server):
    coala mcp-import <TOOLSET> <SOURCES...> or alias coala mcp ...
    SOURCES: local .cwl files, a .zip, or http(s) URLs to a .cwl or .zip.
    Requires the coala package where the MCP server runs (for run_mcp.py).

  • List
    coala mcp-list — list server names.
    coala mcp-list <SERVER_NAME> — print each tool’s schema (name, description, inputSchema).

  • Call
    coala mcp-call <SERVER>.<TOOL> --args '<JSON>'
    Example: coala mcp-call gene-variant.ncbi_datasets_gene --args '{"data": [{"gene": "TP53", "taxon": "human"}]}'

Skills

  • Import (into ~/.config/coala/skills/, one subfolder per source):
    coala skill <SOURCES...>
    SOURCES: GitHub tree URL (e.g. https://github.com/owner/repo/tree/main/skills), zip URL, or local zip/dir.

  • In chat
    /skill — list installed skills.
    /skill <name> — load skill from ~/.config/coala/skills/<name>/ (e.g. SKILL.md) into context.

Chat commands

  • /help, /exit, /quit, /clear
  • /tools — list MCP tools
  • /servers — list connected MCP servers
  • /skill — list skills; /skill <name> — load a skill
  • /model — show model info
  • /switch <provider> — switch provider

MCP on/off

  • All off: coala --no-mcp (or coala ask "..." --no-mcp).
  • One server off: remove its entry from ~/.config/coala/mcps/mcp_servers.json.
  • On: default when --no-mcp is not used; add or restore servers in mcp_servers.json.

Providers and env

Set provider via -p or env PROVIDER. Set keys and URLs per provider (e.g. OPENAI_API_KEY, GEMINI_API_KEY, OLLAMA_BASE_URL). Optional: put vars in ~/.config/coala/env.
coala config — print current config paths and provider/model info.