Revit Api Mcp

Created By
kaitpw10 months ago
Direct access to the Revit API docs and related content.
Overview

Revit API MCP Server

Overview

Because of the absurd surface area of the Revit API, AI often hallucinates classes, methods, properties, or even entire namespaces. Furthermore, useful, but unofficial or uncommon uses of the API are so niche that AI's have no knowledge of it. To curb this, this MCP server provides LLMs access to Revit API documentation and other related content (see Rvt_Docs_Tbc_Embedder). Under the hood, it uses both rvtdocs.com and revitapidocs.com, and if enabled, the Building Coder Blog.

Simply ask your MCP client what the Revit API docs say about something and it will use a combination of tools to explore the API docs on its own.

Features

  • Search Revit API: Search for classes, methods, and properties (or any API entity) in the Revit API documentation.
  • Access Documentation: Retrieve the content of an API entity's docs page either via the url or the entities name.
  • Search/Access TBC Blog: Perform semantic search over a vector space of The Building Coder blog embeddings.

Features (Planned)

  • Code Examples: Get code examples for Revit API usage and make them accessible. See RevitSdkSamples. Or maybe even entire repos, like those from ricuan-io, Nice3point, chuongmep, and of course jeremytammik.
  • More Resources: Add other content to the vector store. Candidates include tbc-related pdfs, random blog posts, and Autodesk University resources.
  • Caching (Unlikely): Cache responses to reduce traffic to the api doc sites.

Server Config

{
  "mcpServers": {
    "revit-api-docs (macos-arm64)": {
      "command": "path/to/Rvt_Docs_MCP-macos-arm64"
    },
    "revit-api-docs (macos-x64)": {
      "command": "path/to/Rvt_Docs_MCP-macos-x64"
    },
    "revit-api-docs (windows)": {
      "command": "path\\to\\Rvt_Docs_MCP-windows.exe"
    },
    "revit-api-docs (with search-library enabled)": {
      "command": "path\\to\\Rvt_Docs_MCP-windows.exe -k 'sk-xxx' -v 'vs_xxx'"
    }
  }
}
Project Info
Created At
10 months ago
Updated At
10 months ago
Author Name
kaitpw
Star
-
Language
-
License
-
Category

Recommend Servers

View All
Trainzilla Mcp

8 hours ago
Shippo
@Shippo

2 days ago
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

a day ago