"How to convert text into a MongoDB query" matching MCP tools:

• nausika_geocode

  Nausika

  Resolve a place 'query' to coordinates (forward) or find nearest places to 'latitude'+'longitude' (reverse). Mediterranean-focused curated DB; forward falls back to OSM/Nominatim globally. Returns name, type, coords, plus similarity (forward) or distance_m (reverse). Example forward: query="Portofino". Example reverse: latitude=44.3, longitude=9.21, radius_m=50000. Chain into nausika_marine_forecast, nausika_tides, nausika_search_places, or nausika_sea_route using the returned coords.

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• web_url_reader

  Inferventis MCP Server

  Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.

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• generate_3d_model

  Sats4AI - Bitcoin-Powered AI Tools

  Convert a single photo into a textured 3D GLB model. Uses Seed3D — generates accurate geometry and materials from one image. Async — returns requestId, poll with check_job_status. 350 sats per model. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='generate_3d_model'.

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• scholarfetch_author_papers

  ScholarFetch

  Expand one author into a deduplicated paper list. This is the main author->paper traversal tool and supports research filters. Use `author_id` when you already know the exact author, or `author_name` plus `candidate_index` after `scholarfetch_author_candidates`. Supported comma-separated `filters`: year>=YYYY, year<=YYYY, year=YYYY, has:abstract, has:doi, has:pdf, venue:<text>, title:<text>, doi:<text>. If you pass `engines`, it must include `openalex`.

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• lookup_reciters

  Tarteel MCP Server

  INTERNAL/preparatory tool — text-only, no widget rendered. NEVER use as the user-facing answer to a 'what reciters are available' question — use list_reciters for that (the default interactive widget). Use this ONLY when EITHER (a) the user explicitly asks for plain text / raw data / no widget, OR (b) you will chain the result into play_ayahs in the same turn without showing the raw list (e.g. user asks to play audio by a named reciter; call this to resolve reciter_id, then call play_ayahs). When in doubt, prefer list_reciters.

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• get_doc

  Dock

  Read a workspace's doc (TipTap rich-text) body. Format is negotiable via `format`: `markdown` (default — CommonMark + GFM, ready to feed to an LLM or render in a non-ProseMirror surface), `content` (TipTap JSON, round-trippable into update_doc for structural edits), `text` (plain text, best for search, summarisation, word-count heuristics), or `all` for the legacy three-in-one shape. Default is `markdown` because it's the slice agents need 95% of the time and the JSON form on a long doc can blow past the agent harness's tool-result token cap. Pass `format: "content"` only when you're round-tripping into update_doc for a structural edit. A workspace can hold any combination of doc and table surfaces, one or many of either kind; omit `surface_slug` to read the primary doc surface, or pass it to target a specific doc tab (use `list_surfaces` to enumerate). An unwritten or absent doc returns the requested format empty (markdown="", content={}, text=""); a `surface_slug` that doesn't match any live doc surface 404s.

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• sieve_dataroom_add

  Sieve

  Add a document to a deal's data room. Creates the deal if needed. This is the primary way to get documents into Sieve for screening. Upload a pitch deck, financials, or any document -- then call sieve_screen to analyze everything in the data room. Provide company_name to create a new deal (or find existing), or deal_id to add to an existing deal. Provide exactly one content source: file_path (local file), text (raw text/markdown), or url (fetch from URL). Args: title: Document title (e.g. "Pitch Deck Q1 2026"). company_name: Company name -- creates deal if new, finds existing if not. deal_id: Add to an existing deal (from sieve_deals or previous sieve_dataroom_add). website_url: Company website URL (used when creating a new deal). document_type: Type: 'pitch_deck', 'financials', 'legal', or 'other'. file_path: Path to a local file (PDF, DOCX, XLSX). The tool reads and uploads it. text: Raw text or markdown content (alternative to file). url: URL to fetch document from (alternative to file).

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• proximens_oracle_get_principle

  Proximens Oracle

  Fetch a single GEO principle by UUID. Free tier returns summary + category + confidence only; Pro/Enterprise tiers return full text, source URL, evidence count, and validation metadata. Use this after search_principles to drill down into a specific principle.

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• lookup_reciters

  Tarteel MCP Server

  INTERNAL/preparatory tool — text-only, no widget rendered. NEVER use as the user-facing answer to a 'what reciters are available' question — use list_reciters for that (the default interactive widget). Use this ONLY when EITHER (a) the user explicitly asks for plain text / raw data / no widget, OR (b) you will chain the result into play_ayahs in the same turn without showing the raw list (e.g. user asks to play audio by a named reciter; call this to resolve reciter_id, then call play_ayahs). When in doubt, prefer list_reciters.

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• web_url_reader

  Inferventis — Financial Data, News & Web MCP

  Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.

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• search_data

  Opendata Koumoul

  Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.

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• resolve_error

  DepScope

  Map error OR free-text query to a verified fix. USE WHEN: user pastes a concrete error/stack (ENOENT, ImportError, build failure) — pass `error`. OR user describes a symptom ('webpack slow', 'pip stuck') — pass `query`. Always prefer this over guessing a fix. RETURNS: exact-match {status, solution, confidence, source_url} or search results [{title, summary, source_url}].

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• web_url_reader

  Inferventis MCP Server

  Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.

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• search_data

  Opendata Ademe

  Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.

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• onyx_browser_click

  onyx-mcp

  Click the first visible button or link whose text matches the query (case-insensitive substring match). Returns whether a match was found and the matched element's text + href. Use after onyx_browser_extract to act on what the page advertised. Demo mode returns synthetic OK. (price: $0.003 USDC, tier: metered)

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• rem-to-px

  Microapp

  Convert REM (relative to root font size) to pixels. Defaults to a 16px base (browser default); pass base_px to use a different root size.

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• transcribe_audio

  Toolora

  Use this tool whenever the user shares an audio file and wants it transcribed to text. Triggers: 'transcribe this recording', 'convert this audio to text', 'what was said in this meeting', 'transcribe this voice note', 'turn this podcast into text'. Accepts base64-encoded audio (mp3, wav, m4a, ogg, flac, webm, mp4, etc.), max 25MB. Returns the full transcript, word count, and character count. Powered by OpenAI Whisper. Free 200 calls/day — no OpenAI API key required; Toolora absorbs the cost.

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• dev_url_decode

  botoi-mcp

  URL-decode a percent-encoded string back to readable text. Use when parsing query parameters, redirect URIs, or encoded form values.

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• baselight_search_tables

  baselight

  Search for tables using a text query and filters. Tables in Baselight have the following format: @username.dataset.table. Tables are grouped into datasets which can be public or private — you can search and use all public datasets as well as the user's private datasets. Search for tables directly when you are unable to find relevant datasets.

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• get-protocol-summary

  Crinkl Commerce MCP

  Get a concise explanation of what Crinkl is and how the protocol works. Use this first if you have no prior context about Crinkl. Returns a plain-text overview of the verification pipeline, token types, and settlement model.

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