DeepSeek Search MCP
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Alternatives to DeepSeek Search MCP
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- AlicenseAqualityCmaintenanceEnables MCP clients to run web searches that return ranked results with titles, URLs, snippets, summaries, and optional extracted page content, and to fetch HTTP or HTTPS pages as Markdown. It runs over stdio as a zero-dependency Python server that uses DeepSeek's official APIs and any supported MCP client.22MIT
- AlicenseAqualityCmaintenanceExposes DeepSeek's Search and Fetch REST APIs as two read-only MCP tools, letting any MCP-capable agent run ranked web searches and retrieve individual pages as truncated Markdown. Works with whichever model the host runs, over stdio or Streamable HTTP.2MIT
- AlicenseAqualityCmaintenanceA local stdio MCP server that exposes DeepSeek's Web Search and Fetch APIs, letting AI clients run structured web queries, fetch page contents, and receive DeepSeek's raw JSON responses unfiltered and untruncated. It supports filtering by site, language, and date range, with configurable timeouts and retries.2MIT
- AlicenseAqualityDmaintenanceExposes DeepSeek's web search and page-fetch tools to any MCP client, letting any LLM run searches with quality signals like rerank score and source authority, plus advanced query syntax. It also retrieves single pages as Markdown, with built-in throttling, retries, and size-conscious summaries.2540 npm1MIT
- AlicenseAqualityAmaintenanceEnables AI agents to perform real-time web search and fetch/parse webpages into clean Markdown through DeepSeek's Search and Fetch APIs. It provides configurable summaries, scoring, and robust retries for integration with MCP-compatible assistants.21MIT
- AlicenseAqualityAmaintenanceEnables AI agents to run web and image searches across nine engines with automatic fallback and ad filtering, fetch pages and PDFs as Markdown, and search WeChat Official Account articles — all without requiring a search account or API key out of the box. Works over stdio or Streamable HTTP with any MCP-capable client.5479 npmApache 2.0
TDQS
Scored across 2 tools
deepseek_search (query the web) and deepseek_fetch (retrieve a specific URL as Markdown) target clearly different actions on different inputs. Descriptions explicitly distinguish them and even separate them from the built-in WebSearch/WebFetch, leaving no realistic misselection path.
Both tools follow an identical provider_verb snake_case pattern (deepseek_search, deepseek_fetch), with the verb element drawn from a small, predictable set. Fully consistent.
Two tools is on the thin side, but for a search-and-retrieve server this is the minimal complete pair and each tool clearly earns its place. No bloat or redundancy.
Search plus fetch covers the core retrieval lifecycle, and fetch includes offset/max_chars/next_offset for paging. Minor gaps only (e.g. no explicit batch or site-scoped search option), but nothing that would block an agent's normal workflow.