MCP Studio

A few days ago, I posted about MCP Studio and how agencies are struggling to give their AI agents (like Claude and Cursor) access to niche, industry-specific software without writing tons of boilerplate code.

The feedback was incredible, and I wanted to share a specific use case that came up repeatedly in the comments: Safely querying client data without exposing PII.

One agency founder mentioned they spend hours pulling custom reports from a legacy CRM. They wanted to let an AI agent do it, but were terrified of dumping the whole CRM schema into the LLM, let alone exposing their clients' email addresses to a third-party AI provider.

Here is how we solved it using MCP Studio's MVP:

1. Ingested the Swagger file: Dropped their CRM's API spec into the proxy.

2. Used Magic Suggest: Instead of giving the AI 200+ endpoints, the AI pruned it down to just the GET /reports and GET /clients intents.

3. Turned on the PII Shield: They toggled on the redaction engine so the AI could analyze the data trends without ever seeing the actual names, emails, or phone numbers of the clients.

It's been amazing seeing founders move from "AI is a fun chat tool" to "AI is executing my actual operational workflows."

If you are still writing Python boilerplate to connect your APIs to MCP, you can try the zero-code proxy here:

https://eleayuen-png.github.io/OpenAPI-to-MCP-Converter-MVP/

What other massive operational bottlenecks are you seeing when trying to automate your agency?

Hey Indie Hackers,

I’ve been following the Model Context Protocol (MCP) hype for a while. It’s incredible for connecting LLMs to external tools, but if you’re an agency or a solo founder using niche software, you’re essentially "locked out."

Unless you want to spend 6 hours writing a custom Python server just to bridge a legacy CRM to Claude, your AI agents are effectively blind.

I built MCP Studio to bridge this gap for the mid-market. It’s a serverless proxy that turns any standard REST API (OpenAPI) into a secure MCP server in under 60 seconds.

Why I built it for founders/agencies:

• Zero Boilerplate: No writing translation layers between JSON and text.

• Context Saving: Most generators dump the whole API docs into the LLM. I built a visual "Pruner" so you only give the agent the 3 or 4 tools it actually needs for the task. No bloat, no hallucinations.

• Secure Proxying: Agencies are (rightly) scared of putting API keys in local config files. MCP Studio acts as a secure vault, injecting headers server-side.

I’m currently in "Build in Public" mode with the MVP. If you're building agentic workflows for clients and hitting a wall with API interoperability, I'd love to hear your use cases.

MCP Studio isn't just a "converter"; it’s a mission to solve the interoperability bottleneck that is currently holding back the "Agentic Paradigm Shift." Here is why it exists:

1. Eliminating "Boilerplate Hell"

Right now, if a developer wants to connect Claude or Cursor to a niche CRM, they have to spend 4 to 6 hours writing a custom Python or TypeScript server. This is "plumbing"—it's repetitive, low-value work that wastes developer weekends. We believe giving an AI agent "hands" should take 60 seconds, not 6 hours.

2. Solving the "Token Tax" (Context Bloat)

Most existing tools "dump" an entire API specification into the LLM. This is a technical disaster.

• Hallucinations: When an LLM sees 100 endpoints, it gets confused and picks the wrong one.

• Cost: You end up paying a "token tax" for thousands of irrelevant lines of documentation. MCP Studio exists to provide a Visual Pruner, ensuring the AI only sees the exact tools it needs to complete the task.

3. The Security Paradox

You cannot simply hand an autonomous agent your raw API keys or store them in plain-text local config files. MCP Studio acts as a Zero-Touch Auth Vault. It allows you to use your tools securely by injecting credentials server-side, so your sensitive tokens never touch the LLM's context window or your local logs.

The Vision

We exist to transform isolated data silos into actionable agentic workflows. Our goal is to make it so that any software with a standard API can become "AI-ready" instantly, allowing founders and agencies to focus on building their business rather than managing the plumbing.