The Model Context Protocol (MCP) lets AI assistants like Claude use your tools directly: read your data, call your APIs, drive your software. I build custom MCP servers so AI agents can work with the systems your business already runs on.
What I build
- MCP servers for your API — your product exposed as clean, safe tools an agent can call.
- Bridges to desktop software — MCP connections to creative and productivity apps, so an agent can operate them.
- Internal data access — agents that can query your database, docs or dashboards with the right permissions.
- Agent workflows — multi-step automations built on top of those tools, with logging and human checkpoints.
Hands-on experience
I use MCP every day in my own work — agents driving 3D software, video editing, image generation, task panels and job searches — and I build the servers and bridges that make that possible. I know where tool design goes wrong in practice, not just in the spec.
How it works
We pick the few actions an agent most needs, design them as tools with clear inputs and safe defaults, and ship a first server you can try in Claude right away. Then we widen the toolset based on what the agent actually uses.
Good fit if
You have a product, internal system or piece of software that AI agents should be able to use, and you want it done by someone who builds with MCP daily.
Tell me what the agent should be able to do. I reply with a proposed toolset.