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MCP Server Development

Custom Model Context Protocol servers that connect AI assistants to your business tools.

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Works with any MCP client Claude Desktop ChatGPT Cursor Windsurf VS Code Gemini CLI
5 MCP servers designed, built, and shipped 4 on npm + 1 in production
29 tools across our published servers finance, economic, SEC, and geo data
4 servers live on public npm yahoo-finance, FRED, EDGAR, geocode
Key Takeaway

MCP (Model Context Protocol) servers are the bridge between AI models and your business tools. I build custom MCP servers that give AI assistants direct access to your APIs, databases, and workflows, turning them from generic chatbots into powerful business tools.

What Is MCP?

Model Context Protocol (MCP) is an open standard created by Anthropic that lets AI models interact with external tools and data sources. Think of it as a USB port for AI, a universal way to connect any AI model to any service.

Before MCP, connecting an AI model to your tools meant building custom integrations for each model. MCP standardizes this: build one server, and every MCP-compatible client (Claude Desktop, VS Code Copilot, Cursor, Continue) can use it.

MCP Servers I’ve Built

  • DataForSEO MCP, Gives AI assistants access to keyword research, SERP analysis, backlink data, and competitor intelligence through natural language
  • MCP, AI-powered web scraping: ask Claude to scrape the pricing page of competitor X and get structured data back
  • Analytics MCP, Connect Google Analytics to AI: query traffic data, generate reports, and identify trends through conversation
  • Chrome DevTools MCP, AI-controlled browser automation: navigate, screenshot, interact with web pages through MCP tools

Use Cases

Internal Tools

Let your team query internal databases, CRMs, and project management tools through AI assistants instead of learning complex UIs.

Customer-Facing AI

Build AI-powered customer support, sales assistants, or onboarding guides that have access to your full product catalog and documentation through MCP.

Developer Productivity

Give Copilot and Cursor context about your codebase, deployment pipeline, monitoring systems, and internal APIs. Stop copy-pasting documentation into chat windows.

Frequently Asked Questions

What is an MCP server?
A server implementing the Model Context Protocol, the open standard that lets AI assistants like Claude and ChatGPT call your tools, query your data, and act in your systems. One server works across every MCP-compatible client.
Which AI clients will it work with?
Any MCP-compatible client: Claude Desktop and Claude Code, ChatGPT, Cursor, Windsurf, VS Code, Gemini CLI, and the growing list of agent frameworks that speak the protocol. Build once, connect everywhere.
How long does a custom MCP server take?
A focused server with 5-10 tools typically ships in 2-3 weeks including testing and integration. Complex auth, multiple data sources, or production hosting add time, which the fixed-scope spec makes explicit upfront.
Do you maintain it after launch?
Yes. The MCP specification still evolves, so we track spec updates, maintain dependencies, and add tools as your use cases grow. Maintenance is scoped in the engagement.
Discuss Your MCP Project

What's included

Custom MCP server development: TypeScript/Node.js or Python MCP servers built to your exact specifications with tool definitions, resource providers, and prompt templates
API integration: Connect AI models to your existing APIs, SaaS tools, databases, and internal services through a standardized protocol
AI agent development: Build autonomous AI agents that can perform multi-step workflows using your MCP servers as their toolkit
Security & auth: Proper authentication, rate limiting, and access control so your MCP servers are production-ready
npm packaging: Publish your MCP servers as installable packages for easy distribution across your team
Documentation & training: Clear docs and team training so your developers can maintain and extend the servers

How it works

  1. Scope and spec

    We map the tools your assistant needs, the data sources behind them, and the auth model. You get a fixed-scope spec before any code.

  2. Build and test

    Server built to the MCP specification with typed tools, input validation, and error handling that LLMs can actually recover from.

  3. Ship and integrate

    Published to npm, your registry, or deployed to your infrastructure with Bearer auth. Wired into the clients your team uses.

  4. Support

    Spec updates tracked, dependencies maintained, and new tools added as your use cases grow.

Frequently Asked Questions

What is an MCP server?
A server implementing the Model Context Protocol, the open standard that lets AI assistants like Claude and ChatGPT call your tools, query your data, and act in your systems. One server works across every MCP-compatible client.
Which AI clients will it work with?
Any MCP-compatible client: Claude Desktop and Claude Code, ChatGPT, Cursor, Windsurf, VS Code, Gemini CLI, and the growing list of agent frameworks that speak the protocol. Build once, connect everywhere.
How long does a custom MCP server take?
A focused server with 5-10 tools typically ships in 2-3 weeks including testing and integration. Complex auth, multiple data sources, or production hosting add time, which the fixed-scope spec makes explicit upfront.
Do you maintain it after launch?
Yes. The MCP specification still evolves, so we track spec updates, maintain dependencies, and add tools as your use cases grow. Maintenance is scoped in the engagement.

Want your tools speaking MCP?

Bring a use case. We'll sketch the tool surface on the call and tell you honestly if MCP is the right fit.

Book a Strategy Call