
mcp-client
Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to avoid context window bloat from tool definitions. Use when interacting with external MCP servers (Zapier, Sequential Thinking, GitHub, filesystem, etc.), listing available tools, or executing MCP tool calls. Triggers on requests like "connect to Zapier", "use MCP server", "list MCP tools", "call Zapier action", "use sequential thinking", or any MCP server interaction.
- Installs
- 138
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/coleam00/second-brain-skills --skill mcp-client- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads mcp-client automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Universal MCP Client
Connect to any MCP server with progressive disclosure - load tool schemas on-demand instead of dumping thousands of tokens into context upfront.
Skill Location
This skill is located at: .claude/skills/mcp-client/
Script path: .claude/skills/mcp-client/scripts/mcp_client.py
Configuration
The script looks for config in this order:
MCP_CONFIG_PATHenv var (custom path)references/mcp-config.json(this skill's config - recommended).mcp.jsonin project root~/.claude.json
Your config file: .claude/skills/mcp-client/references/mcp-config.json
Edit this file to add your API keys. The example file (example-mcp-config.json) is kept as a reference template.
If the user hasn't provided their Zapier API key yet, ask them for it.
Running Commands
All commands use the script at .claude/skills/mcp-client/scripts/mcp_client.py:
# List configured servers
python .claude/skills/mcp-client/scripts/mcp_client.py servers
# List tools from a server
python .claude/skills/mcp-client/scripts/mcp_client.py tools <server_name>
# Call a tool
python .claude/skills/mcp-client/scripts/mcp_client.py call <server> <tool> '{"arg": "value"}'
Workflow
- Check config exists - Run
serverscommand. If error, create.mcp.json - List servers - See what MCP servers are configured
- List tools - Get tool schemas from a specific server
- Call tool - Execute a tool with arguments
Commands Reference
| Command | Description |
|---|---|
servers | List all configured MCP servers |
tools <server> | List tools with full parameter schemas |
call <server> <tool> '<json>' | Execute a tool with arguments |
Example: Zapier
# 1. List servers to confirm Zapier is configured
python .claude/skills/mcp-client/scripts/mcp_client.py servers
# 2. List Zapier tools
python .claude/skills/mcp-client/scripts/mcp_client.py tools zapier
# 3. Call a Zapier tool
python .claude/skills/mcp-client/scripts/mcp_client.py call zapier <tool_name> '{"param": "value"}'
Example: Sequential Thinking
# 1. List tools
python .claude/skills/mcp-client/scripts/mcp_client.py tools sequential-thinking
# 2. Use sequential thinking
python .claude/skills/mcp-client/scripts/mcp_client.py call sequential-thinking sequentialthinking '{"thought": "Breaking down the problem...", "thoughtNumber": 1, "totalThoughts": 5, "nextThoughtNeeded": true}'
Config Format
Config file format (references/mcp-config.json):
{
"mcpServers": {
"zapier": {
"url": "https://mcp.zapier.com/api/v1/connect",
"api_key": "your-api-key"
},
"sequential-thinking": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-sequential-thinking"]
}
}
}
Transport detection:
url+api_key→ FastMCP with Bearer auth (Zapier)command+args→ stdio (local servers like sequential-thinking)urlending in/sse→ SSE transporturlending in/mcp→ Streamable HTTP
Error Handling
Errors return JSON:
{"error": "message", "type": "configuration|validation|connection"}
configuration- Config file not found. Create.mcp.jsonvalidation- Invalid server or tool nameconnection- Failed to connect to server
Dependencies
pip install mcp fastmcp
References
references/example-mcp-config.json- Template config filereferences/mcp-servers.md- Common server configurationsreferences/python-mcp-sdk.md- Python SDK documentation
FAQ
What does the mcp-client skill do?
Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to avoid context window bloat from tool definitions. Use when interacting with external MCP servers (Zapier, Sequential Thinking, GitHub, filesystem, etc.), listing available tools, or executing MCP tool calls. Triggers on requests like "connect to Zapier", "use MCP server", "list MCP tools", "call Zapier action", "use sequential thinking", or any MCP server interaction.
How do I install mcp-client?
Run npx skills add https://github.com/coleam00/second-brain-skills --skill mcp-client in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/mcp-client/ (personal) or .claude/skills/mcp-client/ (project).
Which AI agents can use mcp-client?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is mcp-client safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains mcp-client?
It is published by coleam00 in coleam00/second-brain-skills. It has 138 recorded installs.
More from coleam00/second-brain-skills
pptx-generator
coleam00/second-brain-skills
Generate and edit presentation slides as PPTX files. Also create LinkedIn carousels and manage reusable slide layouts. TRIGGERS - Use this skill when user says: - "create slides for [brand]" / "generate presentation for [brand]" / "make slides for [brand]" - "create a carousel for [brand]" / "linkedin carousel" / "make a carousel about [topic]" - "edit this pptx" / "update the slides" / "modify this presentation" - "create a new layout" / "add a layout to the cookbook" / "make a [type] layout template" - "edit the [name] layout" / "update the cookbook" / "improve the [name] template" - Any request mentioning slides, presentations, carousels, PPTX, or layouts with a brand name Creates .pptx files compatible with PowerPoint, Google Slides, and Keynote. Creates PDF carousels for LinkedIn (square 1:1 format).
sop-creator
coleam00/second-brain-skills
Create runbooks, playbooks, and technical documentation for engineering teams. Use when the user wants to document a process, create a runbook, build operational docs, or formalize any repeatable technical procedure. Triggers on requests like "create a runbook for...", "document this process", "write a playbook", or any technical documentation request.
brand-voice-generator
coleam00/second-brain-skills
Open the skill to read its SKILL.md instructions.
skill-creator
coleam00/second-brain-skills
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
remotion-best-practices
coleam00/second-brain-skills
Open the skill to read its SKILL.md instructions.
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available