apifable
Read the spec. Understand the API. Integrate with confidence.
Power your agent
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Host a copy with our keys and logs.
npx -y [email protected]Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
claude mcp add apifable -- npx -y apifable@1.2.0รันในเทอร์มินัล
{ "mcpServers": { "apifable": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
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apifable is an MCP server that helps AI integrate APIs more smoothly into TypeScript frontend projects. It makes it easy to explore API structure, search endpoints, and generate TypeScript types, giving your AI agent the context it needs to write accurate integration code.
Run apifable init to set up your project configuration:
npx apifable@latest init
This creates apifable.config.json in your project root. The config file should be committed to version control so the spec path is shared with your team.
After the command starts, you can choose between Manual file and Remote URL.
Use this mode if your OpenAPI spec already lives in the project, or if you want to manage spec updates yourself.
init will ask for the local file path, such as openapi.yaml.
This generates the following apifable.config.json:
{
"spec": {
"path": "openapi.yaml"
}
}
You then need to place your OpenAPI spec at that path manually. When the backend API changes, you also need to update that file manually.
Use this mode if your OpenAPI spec is available from a stable remote URL, such as the OpenAPI spec endpoint provided by your backend API docs.
init will first ask for the remote URL, such as https://api.example.com/openapi.yaml (supports yaml and json files), and then ask for the local output path, such as openapi.yaml.
This generates the following apifable.config.json:
{
"spec": {
"path": "openapi.yaml",
"url": "https://api.example.com/openapi.yaml"
}
}
[!NOTE] In this mode,
initalso adds the downloaded local spec path to.gitignoreautomatically, because the file is intended to be refreshed from the remote source. Of course, you can decide for yourself whether to commit it to version control.
You can then run the following command to download the OpenAPI spec from the remote URL to your local path (spec.url → spec.path). Whenever the spec changes, just run it again to refresh:
npx apifable@latest fetch
For non-sensitive headers that can be shared with your team, add spec.headers to apifable.config.json:
{
"spec": {
"path": "openapi.yaml",
"url": "https://example.com/openapi.yaml",
"headers": {
"X-Api-Version": "2"
}
}
}
If downloading the remote OpenAPI spec requires authentication (private API), store secret headers in .apifable/auth.json. This file should not be committed to version control:
{
"headers": {
"Authorization": "Bearer YOUR_SECRET_TOKEN"
}
}
Both apifable.config.json and .apifable/auth.json support ${ENV_VAR} syntax in header values.
{
"headers": {
"Authorization": "Bearer ${MY_API_KEY}"
}
}
.apifable/auth.json headers (overrides same-named keys)apifable.config.json spec.headersAdd the following to your .mcp.json:
{
"mcpServers": {
"apifable": {
"command": "npx",
"args": ["-y", "apifable@latest", "mcp"]
}
}
}
For other AI agents such as Cursor and Windsurf, you can follow the same approach to configure apifable as an MCP server.
Here are some example prompts you can use to explore APIs and build features.
List all APIs
Show me APIs related to posts
List APIs under the Post tag
Show me the API details for post comments
Show me the API details for GET /posts/{id}/comments
Show me the API details for postComments
Implement the post comments feature
Post page: src/pages/posts/[id].tsx
Related APIs:
- GET /posts/{id}/comments (list post comments)
- POST /posts/{id}/comments (create a post comment)
[!TIP] When writing a prompt to build a feature, include relevant context: page paths, component locations, related APIs, and any patterns or examples to follow.
Add the following to your project's AGENTS.md to help AI agents use apifable more effectively:
## API Integration
- **Apifable-first:** MUST use Apifable MCP tools to obtain OpenAPI metadata, endpoint details and TypeScript types; MUST NOT read `openapi.yaml` directly.
The above is a recommended starting point. Feel free to adjust the prompt as needed.
get_spec_infoReturns the API title, version, description, servers, and all tags with their endpoint counts. Start here to understand the shape of an unfamiliar spec.
list_endpoints_by_tagInputs:
tag (string): The tag name to filter bylimit (number, optional): Max endpoints to returnoffset (number, optional): Number of endpoints to skip (default: 0)Returns all endpoints belonging to the given tag. The response includes total, offset, and hasMore fields for pagination. Includes a warning when results exceed 30 items and no limit is specified.
search_endpointsInputs:
query (string): Keyword to search fortag (string, optional): Restrict search to a specific taglimit (number, optional): Max results to return (default: 10)Keyword search across operationId, path, summary, and description. Results are ranked by relevance. If no exact matches are found, automatically falls back to fuzzy search. The response includes a matchType field ("exact" or "fuzzy"); fuzzy results also include a score field per result.
get_endpointInputs (choose one):
method (string) + path (string): HTTP method and endpoint path (e.g. get + /users/{id})operationId (string): Operation ID (e.g. listUsers)Returns the full endpoint object, including parameters, requestBody, and responses, with supported internal component $refs resolved inline.
search_schemasInputs:
query (string): Keyword to search forlimit (number, optional): Max results to return (default: 10)Keyword search across schema name and description. Results are ranked by relevance. If no exact matches are found, automatically falls back to fuzzy search. The response includes a matchType field ("exact" or "fuzzy"); fuzzy results also include a score field per result. Empty results may also include a message field with guidance for the next step.
get_schemaInputs:
name (string): Schema name from components/schemasReturns the full schema with supported internal component $refs resolved.
get_typesInputs (choose one mode):
schemas (string[]): Array of schema names from components/schemasmethod (string) + path (string): HTTP method and endpoint pathoperationId (string): Operation ID (e.g. listUsers)Generates self-contained TypeScript declarations as code text. In endpoint mode it follows supported internal component $refs before collecting schema dependencies. It automatically includes transitive dependencies and does not include import statements.
Mode rules:
schemas, method + path, or operationId$refs (e.g. references to other files or URLs) are not supported.If you think this package has helped you, please consider Becoming a sponsor to support my work~ and your avatar will be visible on my major projects.
MCP server that helps AI agents explore OpenAPI specs, search endpoints, and generate TypeScript types.
{ "mcpServers": { "apifable": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Apifable ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-14 MCP server that helps AI agents explore OpenAPI specs, search endpoints, and generate TypeScript types.