# TextRazor — how to use (mcp.ai)

Connect your TextRazor account and use 6 tools for artificial intelligence straight from your AI agent. Connect with your own API key. TextRazor is a natural language processing API that extracts meaning, entities, and relationships from text, powering advanced content analysis and sentiment detection.

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_textrazor?ms=1787291220000`
Add it as a custom/remote MCP connector in your client (Claude, Cursor, VS Code…), then authenticate when prompted. Once connected, ask the agent to use the server's tools (e.g. `textrazor_account_info`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/textrazor`
Auth: `Authorization: Bearer sk_live_…` — create a workspace API key at https://mcp.ai/settings/api-keys
Discover endpoints: `GET https://api.mcp.ai/api/textrazor/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/textrazor/account/info` — This tool retrieves comprehensive information about a TextRazor account, providing essential details about the account's status, usage, and limits. It returns an Account object containing properties s
- `POST https://api.mcp.ai/api/textrazor/classify/text` — This tool will classify text into predefined categories using TextRazor's classification capabilities. It takes input text, optional cleanup mode and language, and returns a list of relevant categorie
  - body: { text: string, classifiers: string, cleanup_mode?: string, language_override?: string }
- `POST https://api.mcp.ai/api/textrazor/custom/classifier/manager` — This tool manages custom classifiers in TextRazor, allowing users to create, update, and manage custom classification categories.
  - body: { limit?: integer, offset?: integer, operation: string, categories?: object[], category_id?: string, classifier_id: string }
- `POST https://api.mcp.ai/api/textrazor/dictionary/manager` — Manage custom entity dictionaries in TextRazor for enhanced named entity recognition. This tool enables you to create and manage dictionaries of domain-specific entities (e.g., product names, company 
  - body: { entries?: object[], operation: string, dictionary_id?: string }
- `POST https://api.mcp.ai/api/textrazor/extract/entities` — Extract named entities (people, places, companies, etc.) from text using TextRazor's entity extraction API. The tool will identify and classify named entities within the provided text, returning detai
  - body: { text: string, cleanup_mode?: string, language_override?: string, entities_allow_overlap?: boolean, entities_filter_dbpedia_types?: string[], entities_filter_freebase_types?: string[] }
- `POST https://api.mcp.ai/api/textrazor/text/razor/analyze/content` — A comprehensive content analysis tool that combines multiple TextRazor extractors to perform a complete analysis of the input text. This action allows users to analyze text content with multiple extra
  - body: { text: string, extractors?: string[], cleanup_mode?: string, language_override?: string, cleanup_use_metadata?: boolean, cleanup_return_cleaned?: boolean }

## Example prompts
- "What can I do in TextRazor?"
- "Show me a summary of my TextRazor account"

## More
- Page: https://mcp.ai/textrazor
- Agent spec (llms.txt): https://mcp.ai/textrazor/llms.txt
- Postman collection: https://mcp.ai/textrazor/postman.json