Connect Any MCP Server.

MCP Agent Studio is a browser-based AI agent that connects to any Model Context Protocol (MCP) server and lets you query your data in plain English using 60+ AI models including Claude, GPT-5, Gemini, DeepSeek, Mistral, Grok, Qwen, NVIDIA Nemotron, and more. It also runs evals against your server — an auto-generated test suite that proves an AI agent can actually answer questions using your tools. Sign up for free — no credit card required.

An eval is a test that checks whether an AI agent can complete a real task using your MCP server. MCP Agent Studio connects to your server, reads every tool and its schema, and writes an eval suite for you. Running the suite has four phases: connect (handshake and tool discovery), harvest (pull real values from read-only tools so the tasks use genuine data), run (a driver model works your tools like a real client would), and score (grade the answers). Direct evals are decided deterministically by code — schema conformance, JSON-RPC error codes, pagination termination, result caps, idempotency — so a failure is a confirmed defect, not a model opinion. Agentic evals send a plain-English task through the driver model and a scoring model grades the final answer.

Paste your server URL into the Evals workspace and run a suite. Instead of eyeballing a tool list in an inspector, you get a pass/fail report per tool with the evidence behind each verdict: the arguments that were sent, the raw response, and which check tripped. Typical failures it catches are tool descriptions too vague for the model to pick the right tool, list endpoints that ignore their own limit parameter, missing-record cases that return null instead of an error, and agent loops that burn dozens of calls without answering.

No. Tools are classified before anything runs — read-only, idempotent, unknown, or destructive. Anything that could mutate or delete your data is excluded from the run and reported as "untestable" rather than being quietly called, and you review and approve the tool list before the suite is generated. Mutation checks are proved indirectly with a read-only witness tool instead.

Yes. Suites are saved against your organization and versioned, so you can replay one after every schema change and compare the new report against the last run. Writing a suite is charged once per version; replaying it only costs the run, which is why regression checks stay cheap. You can also add your own assertions in plain English alongside the generated ones.

No. MCP Agent Studio is a no-code interface. You paste your MCP server URL, pick an AI model, and start chatting. The agent discovers the available tools automatically and calls them for you as needed.

You can use 60+ models from every major provider, including Claude Opus 4.6, Claude Sonnet 4.6, GPT-5.4, GPT-5.5, Gemini 3.1 Pro, DeepSeek V4, Mistral Small 2603, Grok 4.6, Qwen 3, NVIDIA Nemotron Super 120B, Google Gemma 4, Z.AI GLM 4.5 Air, and more. You can switch models mid-conversation to compare responses on the same task.

An MCP server is a lightweight service that exposes tools (functions, database queries, API calls) over the Model Context Protocol so any AI agent can use them. Popular public MCP servers include GitHub, Supabase, Notion, Slack, Stripe, Postgres, Linear, and Playwright. You can also connect your own custom MCP server over HTTP, SSE, or Streamable HTTP.

MCP Agent Studio is free to sign up — no credit card required. Running AI models costs credits, which you can purchase in packs from your Settings page. New accounts may receive a small starter credit to try the product. Credit costs vary by model; check the Settings › Credits page for current pricing.

Yes. Connect the official Postgres or Supabase MCP server (or any MCP server that wraps your database) and ask questions in plain English: "Show me my top 10 customers by revenue this month." The AI generates the SQL, runs it through the MCP server, and returns the results with a natural-language summary.

Claude Desktop only works with Claude. ChatGPT only works with OpenAI models. MCP Agent Studio works with any model from any provider — swap between Claude, GPT, Gemini, DeepSeek, and Grok on the same MCP server without re-configuring anything. It also runs entirely in your browser with no local installation.

Yes. MCP Agent Studio connects any MCP server (HTTP, SSE, or Streamable HTTP) to GPT-5.4, GPT-5.5, GPT-5 mini, and the rest of the GPT-5 family. Paste your server URL, pick the model, and every tool call streams live — no OpenAI SDK or glue code required.

It depends on your server. Claude Sonnet 4.6 and Opus 4.6 are the strongest default tool-callers; GPT-5.4 leads on structured outputs; Gemini 3.1 Pro handles long tool lists; DeepSeek V4 and GLM 5.1 are the budget picks. Compare Mode in MCP Agent Studio scores all of them on your actual server.

Yes. Official hosted endpoints include Notion (https://mcp.notion.com/mcp), Stripe (https://mcp.stripe.com/), GitHub (https://api.githubcopilot.com/mcp/), Linear (https://mcp.linear.app/sse), and Sentry (https://mcp.sentry.dev/mcp). Paste any of them into MCP Agent Studio, or deploy your own sandboxed hosted MCP server with a live URL in under a minute.

Paste the server URL into MCP Agent Studio, add an auth token if the server requires one, and click connect — the agent lists the tools automatically. Remote HTTP, SSE, and Streamable HTTP transports are all supported, entirely in the browser with nothing to install.

Yes — and with GPT-5, Gemini, Grok, or any of 60+ models. MCP Agent Studio connects the official GitHub MCP server (https://api.githubcopilot.com/mcp/) to whichever model you pick, so you can review PRs or triage issues with Claude and re-run the same prompt on GPT-5 to compare.

Yes. The Model Context Protocol is model-agnostic, and MCP Agent Studio acts as a Gemini MCP client: connect any server and run it with Gemini 3.1 Pro or Gemini 3 Flash. Gemini Flash is one of the cheapest models that still calls MCP tools reliably.

Your MCP server credentials stay in your browser session and are never stored on our servers. Conversations are scoped to your Supabase-authenticated organization. We never train on your data, and you can delete your history at any time from Settings.

Yes — this is one of the core reasons people use MCP Agent Studio. Run the same prompt against Claude, GPT-5, and Gemini side by side, inspect every tool call in the live trace panel, and find the cheapest model that still gives great results. Teams routinely cut inference costs 5–10× this way.

Any MCP server that speaks HTTP, SSE, or Streamable HTTP. That includes official servers for GitHub, Supabase, Postgres, Notion, Slack, Stripe, Linear, Playwright, Filesystem, Memory, Sequential Thinking, and hundreds of community servers. You can also point it at your own custom server deployed on Cloudflare Workers, Vercel, Fly, or anywhere else.

Yes. MCP Agent Studio ships with ready-to-run templates covering Notion, GitHub, Amazon Ads, Jira, Confluence, Sentry, HubSpot, Stripe, Linear, Slack, Supabase, Vercel, Shopify, Cloudflare, Zapier, and more — including multi-server combos like GitHub + Vercel + Sentry and Amazon Ads + Stripe for blended ROAS. Pick a template, add your access token, and start chatting in seconds. Browse all templates at /templates.

Yes. Once you set up a model, one or more MCP servers, and a system prompt, you can save the whole configuration as a named agent with one click. Open it again any time from "My Agents" — your servers, tools and model selection are all restored. Agents can be private or shared with your team.

Export is coming soon. Save your agent and open Export in the studio toolbar to preview a Next.js App Router layout or a Python starter (MCP wiring, prompts, .env.example, deploy targets). Downloadable ZIP packs and one-click deploy will ship in a follow-up release; until then you can explore the preview and recreate wiring manually if you self-host.