# Perigon — MCP server on mcp.ai
> Connect your Perigon account and use 9 tools for news and lifestyle straight from your AI agent. Connect with your own API key. Perigon provides an HTTP REST API for retrieving news and web content data, offering structured data suitable for various applications.

By: mcp.ai · official
Page: https://mcp.ai/perigon

## Connect (MCP protocol)
Remote MCP endpoint (HTTP, streamable): https://api.mcp.ai/p_perigon?ms=1787296080000
Add it as a custom/remote MCP connector, then authenticate when prompted.

## REST API (no MCP client required)
Every tool is also a REST endpoint, authed with a workspace API key.
Discover: GET https://api.mcp.ai/api/perigon/_endpoints   # public; lists every endpoint
Call:     POST https://api.mcp.ai/api/perigon/<endpoint>
  Authorization: Bearer sk_live_…   # create one at https://mcp.ai/settings/api-keys
  Content-Type: application/json
  Body: { …args }   →   { "ok": true, "tool": "<id>", "result": { … } }

## Developer docs
How to use (MCP or REST), markdown: https://mcp.ai/perigon/skill.md
Postman collection (v2.1): https://mcp.ai/perigon/postman.json

## Tools
- perigon_get_articles(q?: string, to?: string, from?: string, page?: integer, sortBy?: string, country?: string, domains?: string, sources?: string, category?: string, language?: string, pageSize?: integer, excludeDomains?: string) — Tool to retrieve a list of news articles based on filters. Use when keywords, sources, or date ranges are specified.
- perigon_get_companies() — Tool to retrieve information on companies in Perigon’s entity database. Use when you need a full list of companies. Use after confirming a valid API key is present.
- perigon_get_journalists(limit?: integer, query?: string, offset?: integer, outlet?: string) — Tool to retrieve journalist profiles including title, Twitter handle, bio, and location. Use when you need detailed journalist info to enrich content with author metadata.
- perigon_get_sources(page?: integer, domain?: string, country?: string, category?: string, language?: string, per_page?: integer, max_stories?: integer, max_traffic?: integer, min_stories?: integer, min_traffic?: integer, exclude_domains?: string, include_domains?: string) — Tool to retrieve a list of media sources with filtering options. Use when you need to list sources by domain, country, category, or traffic metrics.
- perigon_get_stories(q?: string, ids?: string, page?: integer, type?: string, image?: boolean, video?: boolean, domain?: string, sortBy?: string, cluster?: integer, country?: string, not_ids?: string, paywall?: boolean, sources?: string, to_date?: string, category?: string, language?: string, from_date?: string, max_score?: number, min_score?: number, sentiment?: string, cluster_min_score?: number) — Tool to retrieve clusters of related articles covering the same event or topic with aggregate metrics. Use when you need to fetch filtered and sorted story clusters after configuring query parameters.
- perigon_get_topics() — Tool to retrieve all available Perigon news topics. Returns a list of topics that can be used to filter articles or stories. Each topic includes an ID, name, and labels (category/subcategory).
- perigon_get_wikipedia(q: string, page?: integer, size?: integer, language?: string) — Tool to search and filter Wikipedia pages. Use when you have a search query ready and want to retrieve relevant Wikipedia articles.
- perigon_vector_search_articles(query: string, top_k?: integer, filter?: object, vector_options?: object, include_vectors?: boolean) — Tool to perform a vector search on Perigon’s real-time news database. Use when you need to retrieve semantically similar news articles given a natural language query.
- perigon_vector_search_wikipedia(limit?: integer, query: string, include_context?: boolean) — Tool to perform semantic retrieval of Wikipedia pages using vector search. Use after obtaining a search query to find relevant Wikipedia articles.

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

## Links
Docs: https://mcp.ai/docs/mcps/perigon
Website: https://mcp.ai/mcps/perigon