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The Suki developer documentation is available as a hosted search MCP server (Model Context Protocol). Connect it in your AI code editor so the AI can ground answers in published guides, API reference, and SDK docs instead of assuming the answers or fetching from the internet. For Copy page and open-in-AI options on every page, use AI-optimized documentation. For product skills and copy-ready prompts, use AI coding tools.

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What MCP server does not do

  • It does not execute any product APIs on your behalf.
  • It does not replace Partner Token or Suki Token authentication for those APIs.

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Key benefits

Accelerate Your Development

Use the documentation as an MCP service in your AI code editor to assist coding and integration tasks.

Improve Your LLM's Responses

Retrieve information from the documentation in your AI code editor to improve response accuracy.

Reduce Manual Research

Reduce the need for manual research and documentation lookup.

Reduce LLM Hallucinations

Ground responses in current documentation instead of invented endpoints or SDK patterns.

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MCP server URL

Use this URL as the custom connector endpoint:
Copy it from the Documentation MCP dropdown in the top navigation bar, from Copy MCP server URL in the contextual menu on any page, or from the setup snippets below. Agents can also discover the server at https://developer.suki.ai/.well-known/mcp (and /.well-known/mcp.json). Prefer the public URL above when you configure a client manually. The screenshot below shows the Documentation MCP dropdown:
Documentation MCP dropdown in the top navigation bar with install and copy actions for Cursor, VS Code, CLI tools, and MCP URL
The panel lists one-click install actions for Cursor and VS Code, plus copy actions for CLI tools (Claude Code, Codex, Gemini CLI, and others). CLI options show a CLI badge. Use Copy MCP URL for tools that need the endpoint only.

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How the MCP server works

When an AI application connects to the Suki documentation MCP server, it can search indexed site content and retrieve full pages as Markdown while it answers your prompt. That keeps answers aligned with what is published on developer.suki.ai.
  • AI applications can search proactively while generating a response, even if you did not ask them to search.
  • They choose which tool to call from conversation context and relevance to Suki docs.
  • Each tool call runs during generation, so the model can use up-to-date documentation.
Some AI tools support both MCP and skills. MCP gives access to your content. Skills instruct agents how to use that content. Connecting this MCP server also exposes published skill resources for discovery. For product prompts and skill URLs, refer to AI coding tools.

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MCP server tools

Connected agents can use the following tools:
  1. Search: Searches across the site and returns snippets with titles and links. Use this to find matching pages.
  2. Query docs filesystem: Reads a virtual documentation filesystem with shell-style commands (rg, head, cat, tree, and similar). Use this to pull exact sections or full pages.
  3. Submit feedback: Reports a page that is incorrect, outdated, confusing, or incomplete. Mintlify records that as unhelpful feedback for the docs team.
A typical flow is search first, then query docs filesystem on the best matches. The server is read-only for content retrieval, plus optional feedback. It does not call Suki product APIs, mutate your integration, or access private partner data. The server also exposes published skill.md files as MCP resources for discovery. Find install commands and product prompts on AI coding tools guide.

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Search parameters

Optional filters your AI tool may pass when the site supports them:
Suki developer documentation is primarily a single public English site. Your AI tool decides whether to pass these filters.

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How to set up MCP integration

Open MCP Settings in Cursor

  1. Use Command + Shift + P on Mac or Ctrl + Shift + P on Windows to open the command palette.
  2. Search for Open MCP settings and select Add custom MCP. This opens mcp.json.
  3. Add the following configuration:
Or select Connect to Cursor from the contextual menu on any documentation page, or use Install in Cursor from the Documentation MCP dropdown.
Use the Documentation MCP dropdown in the top navigation bar to copy these snippets without retyping URLs or JSON.

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Test your connection

After configuration, ask your AI tool:
You should see Suki documentation tools for search, query docs filesystem, and submit feedback. Then try:
The AI should return relevant pages. If it needs full page text, it can use query docs filesystem on those paths.

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Using multiple MCP servers

You can connect several MCP servers in one AI tool. Connected servers do not inject content until the model calls a search or read tool.
  • Connect only the servers relevant to your current work.
  • Be specific in prompts so the model searches the right server.
  • Disconnect servers you are not using to reduce context usage.

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Troubleshooting

Verify the URL is exactly https://developer.suki.ai/mcp. Check your internet connection and restart your AI tool after configuration.
Confirm the MCP server was added correctly. Try removing and re-adding the server configuration. Check your AI tool’s MCP support documentation. Tool names can be site-specific; ask the model which tools it has after connect.
Try different or more general search terms (for example, “webhook” instead of “session completion webhook payload”). Verify the MCP connection is active. Hidden or noindex pages are not available through search MCP.
If the MCP server returns HTTP 429 Too Many Requests, wait and retry. Mintlify applies per-user and per-site hourly limits on search and filesystem tools. Most clients recover automatically within an hour.

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Next steps

AI coding tools - Skills, prompts, and npx skills add. AI-optimized documentation - Copy page and open-in-AI options. Quickstart - getting-started path.
Last modified on October 16, 2026