How to Connect Your AI Agent to Any Tool Using MCP

Yesterday, three new MCP-related tools hit Hacker News. A dependency-graph MCP server. A local context engine. A tool to turn any MCP server into a CLI. Something is happening here—and most OpenClaw users are missing it.

MCP (Model Context Protocol) is quickly becoming the USB-C standard for AI agents. One protocol. Infinite integrations. And yet, the number one question I see is: "How do I actually connect my agent to [GitHub/Slack/Postgres]?"

This post answers that. With a skill you can download and use today.

The Problem

You have OpenClaw running. You want it to:

• Check your GitHub issues and comment on new ones
• Query your PostgreSQL database and return insights
• Send Slack alerts when something needs attention
• Browse websites and extract data

The traditional answer? Write custom code for each integration. Maintain it. Debug it. Watch it break when APIs change.

The MCP answer? Install a standardized server. Add three lines to your config. Done.

But there's a catch: discovering which MCP servers exist, understanding their requirements, and generating the right configuration is still manual work. That's friction. And friction kills adoption.

The Skill: MCP Connector

I built a skill that removes that friction.

The MCP Connector skill does three things:

1. Discovers available MCP servers from the official registry
2. Configures them with the right environment variables and settings
3. Validates that everything is working before you restart OpenClaw

👉 Download free: github.com/thenatechambers/openclaw-skills-repo/tree/main/skills/mcp-connector

How to Use It

Step 1: Find Available Servers

node skills/mcp-connector/scripts/discover.js

Output:

📦 MCP Servers
============================================================

@modelcontextprotocol/server-github
  GitHub integration - repos, issues, PRs
  → https://github.com/modelcontextprotocol/servers/tree/main/src/github

@modelcontextprotocol/server-postgres
  PostgreSQL database integration
  → https://github.com/modelcontextprotocol/servers/tree/main/src/postgres

@modelcontextprotocol/server-slack
  Slack workspace integration
  → https://github.com/modelcontextprotocol/servers/tree/main/src/slack

... and 10 more

Step 2: Generate Config

node skills/mcp-connector/scripts/configure.js --server github

Output:

{
  "mcp": {
    "servers": {
      "github": {
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-github"],
        "env": {
          "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxxxxxxxxxxx"
        }
      }
    }
  }
}

Step 3: Validate Before You Commit

node skills/mcp-connector/scripts/validate.js --server github

Output:

🔍 Validating MCP server: github

✅ Server is responding

Response preview: {"jsonrpc":"2.0","id":1,"result":{"protocolVersion":"2024-11-05"...

📋 Required Environment Variables:
  GITHUB_PERSONAL_ACCESS_TOKEN: GitHub Personal Access Token with repo scope (✓ required)

Step 4: Add to OpenClaw

Paste the generated config into your claw.json file, set your environment variables, and restart OpenClaw. Your agent now has native access to GitHub (or Slack, Postgres, Puppeteer, etc.).

The Recommendation

Stop writing one-off API integrations. Start using MCP servers.

The Model Context Protocol is winning because it solves a real coordination problem. Before MCP, every AI tool vendor had to build their own Slack integration, their own GitHub integration, their own database connectors. It was wasteful and fragmented.

Now? One protocol. One implementation per service. Reused across OpenClaw, Claude Desktop, and every other MCP-compatible client.

This is the same pattern that made USB-C ubiquitous. The old way had dozens of proprietary chargers. The new way has one port that works everywhere.

The skill I shared above removes the last bit of friction: figuring out which servers exist and how to configure them. With it, you can go from "I wish my agent could use GitHub" to "It's working" in under five minutes.

Why This Matters for Cortex Users

Cortex is built on OpenClaw. That means every Cortex agent can use MCP servers the moment they're available.

This matters because the ecosystem is exploding. In the past week alone:

• Depwire launched with MCP tools for dependency graphs
• Context Harness shipped a local-first context engine with MCP support
• MCPX turned the protocol into composable CLI commands

Each new MCP server is a new capability your Cortex agent can access—without waiting for Cortex to build it, without writing code, without maintenance overhead.

Your agent's capabilities now grow at the speed of the open-source ecosystem. That's the power of standards.

---

Want to deploy your own AI agent that runs skills like this automatically? Sign up for Cortex →

---

Quick Reference: Popular MCP Servers

| Server | What It Does | Use Case | |--------|--------------|----------| | github | Read repos, create issues, manage PRs | Automated issue triage, PR summaries | | postgres | Query PostgreSQL databases | Natural language database queries | | slack | Send messages, read channels | Team alerts, daily digests | | puppeteer | Browser automation | Data extraction, screenshot testing | | filesystem | Safe file operations | Document processing, code generation |

All of these work with the MCP Connector skill. Download it, try one, and see how fast your agent's capabilities expand.