"A system for semantic search in code repositories" matching MCP tools:

• map_icd10_to_icd11

  Medical Terminologies MCP

  Authoritative ICD-10 → ICD-11 mapping using WHO transition tables (release 2025-01, bundled with the server). Returns the primary 1:1 ICD-11 category for the ICD-10 code plus any alternative ICD-11 candidates that WHO documents (some ICD-10 concepts split into multiple ICD-11 entities). For each mapping, includes the ICD-11 code, title, chapter, and the Foundation URI / Linearization URI for navigating to the full entity definition. Use this for clinical coding, billing migration, retrospective analysis, and any workflow that needs authoritative mapping rather than text-search candidates. Coverage: 11,243 ICD-10 categories (excludes chapters and blocks like "A00-A09" which aren't used in clinical coding). Provide a code like "E11" (Type 2 diabetes), "I21" (Acute MI), or "A07.8" (4 alternatives in WHO's table). Both dotted ("A07.8") and undotted ("A078") forms are accepted. Returns "no mapping" when the code isn't in the WHO category-level table — that's the honest answer rather than a fuzzy search fallback.

  Connector

• hs_code_lookup

  FreightUtils MCP Server

  Search 6,940 WCO Harmonized System (HS 2022) commodity codes — the 6-digit international customs classification layer. The first 2 digits are the chapter, 4 the heading, 6 the subheading. Provide ONE of: query (free-text description search, min 2 chars), code (2-6 digit lookup, returns the code plus its hierarchy), or section (Roman numeral I-XXI to browse a section). Behavior: read-only; description search is keyword-based against official HS descriptions, so everyday product words can return zero rows — count 0 with an empty results[] is a valid answer (e.g. "laptop" and "computers" find nothing; "automatic data" matches the official phrasing "automatic data processing machines"); prefer the formal tariff wording. Rate-limited (anonymous use: 25 requests/day per IP): a 429 error body carries retry_after_seconds and a Retry-After header — back off and retry, or call get_subscribe_link for higher limits. Returns: the query/code echo, count and results[] (hscode, description and hierarchy context) under result, plus confidence, _source and citation (the FreightUtils v1 response envelope). Limitations: the 6-digit international level only — national tariff lines (8-10 digits) and duty rates are set per country; classification here is indicative, not a binding ruling. Related: uk_duty_calculator (duty/VAT for a code found here), ics2_check (EU ENS goods-description quality — a different check entirely).

  Connector

• find_examples

  Senzing

  Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.

  Connector

• 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.

  Connector

• semantic_search

  Zoning Signal

  Semantic search across the full corpus — every place dossier, corridor signal, meeting reading, and named-pattern brief. Returns results ranked by cosine similarity in a 1024-dimensional embedding space (Voyage AI 4 + Supabase pgvector). Use when the agent does not know the canonical entity slug or named-pattern title in advance — the search returns the readings whose semantic structure best matches the natural-language query, with type, title, similarity, and resolved URL per hit. Threshold 0.55, top 12.

  Connector

• echo_facility_search

  Epa Echo

  Search EPA-regulated facilities by name, state, ZIP code, city, or industry code. facility_name uses a case-insensitive starts-with match; prepend % for a contains search (e.g., "%Exxon%" finds any facility with "Exxon" in its name). Combine at least two filters — a bare state is rejected upstream for large states ({state: "TX"} alone matches ~344,000 facilities and errors). Good queries: {facility_name: "%Exxon%", state: "TX"}, {city: "Baytown", state: "TX"}, {zip: "94025"}, {naics: "3251", state: "TX"}. Returns facility IDs, addresses, lat/long, compliance status, inspection/enforcement counts, and total penalties.

  Connector

• collection.search

  DocImprint

  Semantic (vector) search across documents in a collection. Returns ranked text chunks with relevance scores. Free — no credits consumed. Use when you need raw matching chunks from a collection. For a synthesized cited answer from the same context, use collection.ask instead. PREREQUISITE: Collection must be populated via collection.add_document and async indexing must complete (poll job.status) before results appear. Returns: { results: [{ bundle_id, chunk_id, text, score: number (0–1), title? }] } Example prompts: - "Search my Q4 Contracts collection for mentions of liability cap." - "Find the clause about data retention in my due diligence docs." - "Search for revenue numbers across my quarterly reports."

  Connector

• glim_github_search

  glim.sh

  Search GitHub repositories, conversations (issues+PRs), or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos). Returns compact text by default; pass format='json' for full structured data.

  Connector

• resolve_product_code

  EU Trade Explorer

  Resolve a free-text query or CN code(s) into validated product code(s) with descriptions -- the recommended first step before using a code as `product` in any other tool's `query`. Saves the search -> validate -> (optional) subtree round-trip: a bare keyword runs a search, a single code (or comma-separated list) is validated and described directly. Tip: Comext/CN nomenclature is frequently coarser than a colloquial product name (e.g. there is no code for "glass jars" alone -- only heading 7010, which bundles jars with bottles, flasks and closures). Check `has_subcodes` and, if useful, set `include_children=true` to see whether a finer sub-code is actually a better match before committing to one code for a whole report.

  Connector

• find_exact_text

  Reecopedia

  Find literal occurrences of an exact string in the corpus — article numbers, regulation ids, precise wording (e.g. "Article 8(3)", "2024/1781"). Complements semantic `search`: use this when you need the exact string, not the concept. Returns one match per (file, page) with an occurrence count and a text snippet; read the full page with `fetch`. Scans the literal chunk text of both indexes the semantic search serves (the two chunkings differ, so some passages exist in only one); the synthetic contextual enrichment is NOT scanned — it is not document text.

  Connector

• get_sub_domains

  AnySearch

  This is Anysearch's domain discovery tool. IMPORTANT: Step 1 of vertical search. REQUIRED before any search that uses a domain. Returns valid sub_domains and sub_domain_params for the specified domain(s). Call this when the query targets a specialized vertical or needs structured parameters: stock prices, financial data, academic papers, legal cases, medical/drug info, flight status, weather, exchange rates, geographic POIs, code repositories, or any domain where a structured identifier (ticker, DOI, CVE, IATA, coordinates) is involved. ## When to call — pick the domain(s) that match what the user is asking about: resource social_media finance academic legal health business security ip code energy environment agriculture travel film gaming ## Input — choose from the list above and pass via the domain or domains parameter: - domain: single domain string (use only when 100% certain the query is single-domain) - domains: batch query for up to 5 domains in one call (takes priority over domain) 🏆 ALWAYS prefer the `domains` (plural, array) parameter. Pass ALL potentially relevant domains at once — even for seemingly single-domain queries, consider related domains: - Query about "cryptocurrency regulations" → domains=["finance", "legal", "security"] - Query about "best gaming laptops" → domains=["gaming", "tech", "ecommerce"] - Query about "climate change impact on agriculture" → domains=["environment", "energy", "academic"] ## Returns Markdown table filtered to the specified domains: sub_domain | description | params ## CRITICAL: How to use results - sub_domain is the PRIMARY routing key — always pass it to search - params column shows available structured parameters — pass them via sub_domain_params in search, NEVER embed in query - If multiple sub_domains returned (especially from multiple domains), use batch_search — one query per sub_domain — instead of multiple sequential search calls - Params marked (required) in the output MUST be passed when using that sub_domain in search. If a required param is not applicable to your query, pass it as an empty string (key: "") — do not skip it.

  Connector

• search

  MedRates

  Search for medical procedure prices by code or description. Use this for direct lookups when you know a CPT/HCPCS code (e.g. "70551") or want to search by keyword (e.g. "MRI", "knee replacement"). For code-like queries → exact match on procedure code. For text queries → searches code, description, and code_type fields. Supports filtering by insurance payer, clinical setting, and location (via zip code or lat/lng coordinates with a radius). NOTE: Results are from US HOSPITALS only — not non-US providers, independent imaging centers, ambulatory surgery centers (ASCs), or other freestanding facilities. Args: query: CPT/HCPCS code (e.g. "70551") or text search (e.g. "MRI brain"). Must be at least 2 characters. code_type: Filter by code type: "CPT", "HCPCS", "MS-DRG", "RC", etc. hospital_id: Filter to a specific hospital (use the hospitals tool to find IDs). payer_name: Filter by insurance payer name (e.g. "Blue Cross", "Aetna"). plan_name: Filter by plan name (e.g. "PPO", "HMO"). setting: Filter by clinical setting: "inpatient" or "outpatient". zip_code: US zip code for geographic filtering (alternative to lat/lng). lat: Latitude for geographic filtering (use with lng and radius_miles). lng: Longitude for geographic filtering (use with lat and radius_miles). radius_miles: Search radius in miles from the zip code or lat/lng location. page: Page number (default 1). page_size: Results per page (default 25, max 100). Returns: JSON with matching charge items including procedure codes, descriptions, gross charges, cash prices, and negotiated rate ranges per hospital. Only high-confidence results (with at least one usable price) are included. Each result includes last_updated (ISO date of the per-hospital MRF ingest) and mrf_date (ISO date the hospital self-reported in the MRF file). When all results are filtered out, filtered_low_confidence=true is set so the agent can say "no high-confidence prices found" rather than asserting that no prices exist.

  Connector

• get_icon

  Supericons

  Retrieve one exact SVG icon using an exact ref returned by search_icons, recommend_icons, or preview_icons. Do not guess icon IDs. Use search_icons first if the user only described a concept. Returns SVG code, explicit public library labels, visual preview URL, and public semantic guidance for the exact icon.

  Connector

• search_code

  Github

  Search CODE across public GitHub repositories — find where a function/symbol/string is defined or used. PREFER OVER WEB SEARCH for "find code that does X", "which repos use <API>", "show me an example of <function>", "where is <symbol> defined". Supports GitHub code-search qualifiers right in the query: repo:owner/name, org:name, user:name, language:go, filename:Dockerfile, path:src, extension:ts, in:file. Returns matching files with repo, path, and URL. Note: indexes the default branch only, ignores very common terms, and is capped at ~10 searches/minute.

  Connector

• get_vehicle_booking_link

  gondola

  Get a Gondola.ai deep link for a specific vehicle from search results. Returns a link to Gondola's checkout for this vehicle, where the traveler reviews the rate and completes the reservation on the web. This is the booking path for this connection. (Connections belonging to an approved booking partner — which requires the mcp:book OAuth scope — additionally get an in-conversation option here.) Args: search_id: Search ID from search_vehicles. vendor_code: Vendor code from search results. rate_code: Rate code of the selected vehicle. pickup_datetime: Pickup date and time in ISO format. dropoff_datetime: Drop-off date and time in ISO format. Returns: Booking instructions tailored to the user's auth status.

  Connector

• medcode_get_code

  medical-codes-mcp-server

  Decode one or more US medical codes to their official descriptions across ICD-10-CM (diagnoses), ICD-10-PCS (inpatient procedures), HCPCS Level II (supplies/drugs/services), and RxNorm (drugs, by RXCUI). Also decodes a National Drug Code (NDC) directly to its RxNorm product offline, tagged `source: "NDC"` — hyphenated in an FDA segment configuration (4-4-2, 5-3-2, 5-4-1, or the 11-digit 5-4-2) or as bare 10/11 digits; any other segment widths are malformed and stay unresolved. Auto-detects the system from each code's shape; pass an explicit `system` only when a value is genuinely ambiguous. Accepts 1–50 codes and returns partial success: resolved codes in `found`, unresolved in `notFound` with a per-code reason, so one bad code never fails the batch. Set `includeHierarchy` to attach each code's parent and immediate children (with a `childrenTruncated` flag when a code has more children than the cap returns — walk the full set via medcode_browse_hierarchy or medcode_map_codes). The resolved `system` is echoed on every result for chaining into medcode_map_codes or a billability check; a code string that also exists in another bundled system carries `alsoInSystems` naming it, so a single answer to a colliding code is never mistaken for the only one.

  Connector

• medcode_check_code

  medical-codes-mcp-server

  Validate whether a US medical code exists, is current, and is billable in the active bundled release. Returns a discriminated status — valid_billable, valid_not_billable, valid_header, or terminated — with a `whyNot` explaining non-billable and terminated cases (e.g. "valid ICD-10-CM category but not billable — submit a more specific child code"). This is the detail a coder needs before submitting a claim. Auto-detects the system from the code's shape; pass an explicit `system` to disambiguate. A non-billable or terminated code is a successful result with a whyNot, not an error — only a code that exists in no bundled system raises unknown_code. A code string that also exists in another bundled system carries `alsoInSystems` naming it, since the verdict applies only to the system that answered.

  Connector

• medcode_browse_hierarchy

  medical-codes-mcp-server

  Walk a US medical code system's hierarchy for discovery without a search term. With no `node`, returns the top-level entries (ICD-10-CM categories, HCPCS range buckets, or ICD-10-PCS first-axis values). With a `node`, returns its immediate children. ICD-10-CM and HCPCS use a prefix hierarchy (a shorter code is the parent of a longer one); ICD-10-PCS is axis-based — each of its 7 characters is an independent axis (section, body system, root operation, body part, approach, device, qualifier), but only the top-level Section axis is browsable (omit `node`): positions 2–7 are context-dependent on the preceding axis path and are not enumerable from a flat partial code. Lets an agent orient in an unfamiliar system or enumerate a category's specific codes. A large child set paginates: when the response carries a `nextCursor`, pass it back as `cursor` to fetch the next page.

  Connector

• SearchDocumentKeyword

  equibles

  Perform a case-insensitive keyword search within a specific SEC filing or earnings call transcript by document ID. Returns matching lines with surrounding context and line numbers, making it ideal for finding exact terms, figures, or phrases that semantic search might miss. Typographic punctuation is folded before matching, so a plain-ASCII keyword (e.g. "world's") matches the smart punctuation stored in filings. The header reports the total number of matching lines even when only the first ones are shown. Use this after ListCompanyDocuments to locate precise occurrences of a keyword (e.g., a revenue figure, risk factor term, or executive name) within a known document. Complements semantic search tools by providing exact text matches rather than meaning-based results. Use ReadDocumentLines to read broader sections around matches.

  Connector

• ReadDocumentLines

  equibles

  Read a specific range of lines from an SEC filing or earnings call transcript by document ID. Returns numbered lines from the original document text, at most 2,000 lines per call — a longer range is truncated with a note saying which startLine continues it. Use this to read sections of a filing that were identified by SearchDocumentKeyword (by line number) or by semantic search tools (by approximate line number shown in excerpts). Ideal for reading full tables, paragraphs, or sections that may have been truncated in search results. The document ID and line range must be known beforehand — use ListCompanyDocuments to find documents and SearchDocumentKeyword or semantic search to identify relevant line numbers.

  Connector