"A tool for exploring code graphs across multiple projects" matching MCP tools:

• find_equivalent

  Medical Terminologies MCP

  Ranked unified search for equivalent terms across multiple medical terminologies. Use this tool to: - Find the same concept in different coding systems - Compare how terminologies represent a concept - Support terminology mapping and data integration Searches across: ICD-11, SNOMED CT, LOINC, RxNorm, and MeSH. Set `target_terminologies` to limit which are searched, or set `source_terminology` to exclude one (e.g. when you already have a code from that terminology and want equivalents elsewhere). The two combine: source is subtracted from targets. `limit` caps candidates per terminology (default 5, max 10). Every candidate carries `match_score` (lexical similarity to the search term, 0-1) and `rank` (global position across all searched terminologies) — both computed by this server, since upstreams don't expose comparable relevance scores. Candidates from different terminologies whose titles are lexically identical are clustered in `groups` — a strong same-concept signal (absence of a group is NOT evidence of non-equivalence). Searches upstreams in English. For official pt-BR content, use the dedicated tools: `icd11_search`/`mesh_search` accept `language: "pt"`, and `cid10_search` is natively Portuguese.

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• compare_translations

  Tripitaka MCP (hosted)

  Compare every available translation for a single segment. 💡 **Use this tool when:** - The user asks about the meaning/translation of a single Pāli line and wants to see multiple translators side-by-side. - Checking how different translators interpret the same line — technical terms like `dukkha`, `anattā`, `nibbāna` carry nuance that varies across translations. - Academic work that needs to quote multiple translations. 🔍 **vs `get_sutta`:** this tool targets a **single segment** (line level); `get_sutta` returns the **whole sutta**. To compare a whole sutta you'd call `compare_translations` for each segment. 📋 **segment_id format:** `<sutta_id>:<paragraph>.<line>`, e.g. `mn1:171.4` (Mūlapariyāyasutta paragraph 171 line 4 — "Nandī dukkhassa mūlaṁ"). Find segment_ids via `get_sutta` or search results. ⚠️ **Current state:** the `translation` table is mostly empty (the DB only loads default Pāli + English from bilara). `total_editions` is usually 0; `text_pali` and `text_english` are always populated. Thai editions will be added later.

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• lookup_postal_code

  Postal Lookup MCP

  Resolve a postal/ZIP code to its place name(s), state/region, and coordinates. `country_code` is a 2-letter ISO code (US, GB, DE, ...); `postal_code` format varies by country (e.g. "90210" for the US, "SW1A 1AA" style outward codes for the UK). Use for "what city is ZIP 90210 in", "where is postal code X in country Y", or any question that needs a place name/region/lat-lon from a postal code -- not for the reverse (place name to postal code) or for full street address lookup. Some postal codes span multiple places, in which case all of them are returned. Returns an error dict (never raises) if the code isn't recognized for that country.

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• projects_search

  Epinu

  Search Epinu real-asset projects. Returns bounded summaries only; call projects_get_deep_dive for detailed packets. Results include public projects plus the token owner's own archived, draft, or unpublished projects for duplicate checks; another owner's unpublished projects are never returned. Available without a token for public results only.

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• search_locations

  whentofly

  Resolve a city or airport name or code before searching flights. Returns typed values such as city:SHA to search every catalog airport in Shanghai or airport:SHA for Hongqiao only. Pass the selected value unchanged to search_flights. Ask the traveler when multiple results are plausible.

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• list_hospital_code_costs

  MedPrice AI

  Returns cost stats for every hospital with a matching chargemaster entry for a code_type/code. Use this instead of calling get_hospital_chargemaster_cost once per hospital when comparing prices for the same procedure across hospitals (e.g. "which hospital has the cheapest MS-DRG 652?"). Defaults to returning every matching hospital (currently at most a few hundred) in one call. If the response's next_page_token is non-empty, the result set was truncated: call this tool again passing that exact value as page_token to get the next page, and keep doing so until next_page_token is empty - do not stop after one page and conclude a hospital has no data for this code. The response's total_count field (total across all pages) can be compared against how many results you've accumulated so far as a completeness check.

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• factreason_integration_brief

  FactReason

  Compile one callable third-party API brief: base URL, auth scheme, required parameters and types, request body, and documented response codes. Service is required and endpoint optionally narrows the operation. Set responseFormat="compact" for tokenizer-measured context savings; the backward-compatible default returns the full brief plus compact form. Uses metered access. Prefer factreason_api_schema when exploring multiple endpoints.

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• explore

  ThinAir Geo

  BROWSING / DISCOVERY search — cities, neighbourhoods, or mixed venues near a location. Use this when the user is exploring a REGION rather than looking for a specific category. Supports population filtering ('cities > 100k'), distance/population sorting, and layer filtering (locality / neighbourhood / venue / address / street). For specific POI categories (gas, food, charging, etc.), use `search_places` instead.

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• generate_wallet

  Blueprint Agentic Staking (Solentic)

  Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.

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• get_workspace_summary

  FlowCastle

  Return a compact application, flow, sequence, operation, and bot summary — the cheapest way to orient in a workspace. Read-only, no side effects. Deliberately omits variables and full flow graphs: use get_variable_context for variables, get_flow_context for a flow's topology, and get_application_context when you need flows, bots, and variables together.

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• steam_compare

  SteamGPT

  Two players side by side: identity, account age, visibility, Steam bans, FACEIT and shared friends (compared over the full friend lists). HEAVIEST tool - it builds two summaries plus both friend graphs; for a single player prefer steam_summary.

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• query_power_interconnection_queue_nyiso_v1

  osint

  Query the NYISO generator + load interconnection queue — New York ISO's public waiting line of projects that have REQUESTED to connect to the New York grid. Uniquely among ISOs, NYISO publishes a Load Projects tab — load interconnection requests (large-load demand), served as-reported — and since its 2026-07 edition tags each load request with its own `End-Use` class (`end_use`, e.g. DAT / DAT-AI / DAT-CM, served verbatim). Returns cited, project-level records with NYISO's full published structure across every lifecycle tab (nine tabs through 2026-06; seven since NYISO's 2026-07 restructure): summer and winter peak megawatts kept SEPARATE (`sp_mw` = SP, the max summer output; `wp_mw` = WP, the max winter output), the Load Projects tab's `peak_mw_load` with NYISO's own `end_use` class and `sis_bundle` study-batch code (both 2026-07 onward, null before), the as-reported study-phase code (`study_status_code` — NYISO's numeric key, labeled `S` through 2026-06 and `Project Status #` / `NYISO Status` since), the request `record_type` and `project_type`, the `type_fuel` codebook, the energy-storage capability, the NYISO load `zone` (A–K), location (`state`, `county`, derived `county_fips`, `point_of_interconnection`, `utility`), and lifecycle dates (`ir_date`, `last_update`, the milestone dates, and the Year/Qualifier `proposed_cod` kept verbatim). Group or filter by `application_status`, `sheet_name`, `state`, `county_fips`, `study_status_code`, `record_type`, `type_fuel`, `zone`, `utility`, `studies_available`, or `end_use`; filter `ir_date` by the `ir_date_from` / `ir_date_to` range. Pass each parameter as a top-level key of `params` (flat — not nested). Example: `{"application_status": "ACTIVE", "type_fuel": "S"}` for active solar requests; `{"sheet_name": "Load Projects"}` for the load interconnection requests; `{"end_use": "DAT-AI", "application_status": "ACTIVE"}` for the load requests NYISO itself codes DAT-AI; `{"group_by": ["application_status"]}` for requested MW and project counts by lifecycle. Returns JSON aggregates with citations and optional row-level records when `include_records` is true; every value carries `source`, `as_of`, and a `source_row` verifiable with get_source_evidence_v1. `sp_mw` / `wp_mw` / `peak_mw_load` are REQUESTED capacity, not built: historically the large majority of queued megawatts withdraw before they are built, so the queue is withdrawn-dominated. NEVER read a queue-MW total as installed or operating capacity — it is additive across distinct project-rows but is a REQUESTED total only. NYISO publishes summer (SP) and winter (WP) peak MW separately — they are served under NYISO's own names and never blended into one nameplate. Scope by `application_status` (ACTIVE / WITHDRAWN / IN_SERVICE / AFFECTED_SYSTEM / AFFECTED_SYSTEM_WITHDRAWN — the lifecycle tab's reading, overridden to the withdrawn form when a row carries NYISO's own status code 0, per the workbook's printed '0=Withdrawn' key) or by `sheet_name`; the `In Service` tab is the built reading. A project may appear on more than one tab (the grain is sheet + queue_position), so the counts are project-rows, not deduped projects. For built/operating capacity use query_power_capacity_v1. NYISO only — never summed, deduped, or compared across ISOs. For the MISO interconnection queue use query_power_interconnection_queue_v1; for PJM use query_power_interconnection_queue_pjm_v1 (or query_power_interconnection_queue_pjm_cycle_v1 for PJM's cluster/cycle grid); for the CAISO (California) queue use query_power_interconnection_queue_caiso_v1; for the ISO-NE (New England) queue use query_power_interconnection_queue_isone_v1; for the ERCOT (Texas) queue use query_power_interconnection_queue_ercot_v1; for the SPP (central US) queue use query_power_interconnection_queue_spp_v1. NYISO's Load Projects tab is served as-reported: `end_use` is NYISO's OWN classification (NYISO publishes no key for the codes), and this tool does NOT infer an end use NYISO did not print — interpretation beyond the code is the analyst's, from cited rows.

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• batch_search

  AnySearch

  This is Anysearch's parallel search tool. Parallel search — run multiple Anysearch queries in a single call. Prefer this over multiple sequential calls when you have 2–5 queries. Saves context space and returns all results at once. Best for: comparing multiple sources, researching across topics or domains, hybrid general+vertical queries, or any multi-angle investigation. ## When to use Use batch_search instead of multiple sequential search calls when you have 2–5 independent queries. 🏆 PRIMARY use case: After get_sub_domains(domains=[...]) returns sub_domains across multiple domains, use batch_search to send one query per sub_domain in parallel. This is more efficient than sequential per-domain search calls. Also useful for ambiguous / fuzzy queries within a single domain: after get_sub_domains, use batch_search to explore multiple sub_domains in parallel. ## Constraints - Maximum 5 queries per call - Each query item follows the search tool parameter structure (query is required; domain, sub_domain, sub_domain_params are optional. For general queries, omit all domain fields. For vertical queries, domain + sub_domain + sub_domain_params MUST come from get_sub_domains(domain=<domain>) output — same rules as the search tool) - Queries run in parallel; a single query failure does not block others - REQUIRED PARAMS: Same rule as search — when a required param from get_sub_domains is not applicable, pass it as an empty string (key: ""). Never skip required params. ## Examples ### Single-domain batch (multiple sub_domains) Instead of: search(query="latest TSLA earnings", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA stock forecast", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA analyst rating", domain="finance", sub_domain="finance.us_stock") Use: batch_search(queries=[{query:"latest TSLA earnings", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA stock forecast", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA analyst rating", domain:"finance", sub_domain:"finance.us_stock"}]) ### Multi-domain batch (after get_sub_domains with multiple domains) After: get_sub_domains(domains=["finance", "health", "legal"]) Use: batch_search(queries=[ {query:"AI regulation impact on healthcare stocks 2025", domain:"finance", sub_domain:"finance.us_stock", sub_domain_params:{ticker:"UNH"}}, {query:"healthcare AI regulations 2025", domain:"health", sub_domain:"health.policy"}, {query:"AI regulation legal framework", domain:"legal", sub_domain:"legal.legislation"}]) ### Hybrid: general + vertical in parallel (universal pattern for any borderline query) Use this whenever you are unsure if the query is pure encyclopedia or domain-specific — fire BOTH channels in batch_search: batch_search(queries=[ {query:"..."}, // general — no domain {query:"...", domain:"...", sub_domain:"..."}]) // vertical channel(s) This applies universally: classical texts, financial concepts, legal theories, historical events, scientific discoveries, medical topics — any query where domain knowledge could enrich the encyclopedia answer.

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• fda_search_510k

  FDA Data MCP

  Search FDA 510(k) clearances across all companies. Filter by company name (fuzzy match), product code, decision code (e.g., SESE=substantially equivalent), clearance type (Traditional, Special, Abbreviated), and date range. Returns clearance number (K-number), applicant, device name, decision date, and product code. Related: fda_device_class (product code details and classification), fda_product_code_lookup (cross-reference a product code across 510(k) and PMA), fda_search_pma (PMA approvals for higher-risk devices).

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• fda_device_class

  FDA Data MCP

  Lookup FDA device classification details by product code. Returns device name, device class (I/II/III), medical specialty, regulation number, review panel, submission type, and definition. Requires: product code (3-letter code from 510(k), PMA, or device product listings). Related: fda_product_code_lookup (cross-reference across 510(k) and PMA), fda_search_510k (clearances for this product code), fda_search_pma (PMA approvals for this product code).

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• search_airports

  airports

  Look up an airport by city name (e.g. "Tokyo", "New York", "London") OR by 3-letter IATA code (e.g. "JFK", "LHR"). City lookup uses a bundled map of the top ~150 international hubs; cities with multiple airports return all primary ones. For airports not in the bundle, pass an IATA code or use the aviationstack pack for full-text name/country search.

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• find

  Fast.io

  Unified search across a workspace or share — ONE query, results GROUPED BY TYPE into buckets (files, metadata [workspace only], comments), each independently paginated and health-reported. Call action='describe' for the full action/param reference. This is the grouped SUPERSET; for a single result type prefer the narrower tools: `storage action=search` (files only), `metadata action=search` (lexical metadata fields only). The code-mode `search` tool searches the API endpoint catalog, not your content.

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• list_stream_objects

  mcp

  Lists stream objects in a given stream. * Parent parameter is in the form 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-stream'. * Not all the details of the stream objects are returned. * To get the full details of a specific stream object, use the 'get_stream_object' tool.

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• generate_quiz

  Vocab Voyage

  Use this when the user wants to practice, be quizzed, or test their knowledge across multiple words at once. Generates a 1–10 question multiple-choice quiz for a test family (isee, ssat, sat, psat, gre, gmat, lsat, general). Renders the interactive Vocab Voyage quiz widget on supporting hosts; per-answer taps persist mastery for signed-in users. Do not use for definition lookups — call get_definition instead. Do not use for spaced-repetition flashcards — call get_flashcards instead.

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• auth_request_otp

  Kash.click

  Step 1 of 2 for in-conversation authentication. Sends a one-time password (OTP) to the user's email address. If the user has multiple accounts, provide accountID (obtained from account_list) to target the right one. On success, an OTP code is sent by email — then call auth_login_with_otp with that code.

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