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213,242 tools. Last updated 2026-06-19 14:13

"Understanding Code Relationships and Dependencies" matching MCP tools:

  • Search banks and financial institutions by name, SWIFT/BIC code, or country. Covers both SWIFT-connected banks and non-SWIFT financial institutions (e-money issuers, payment processors, MFOs, brokerages, VASPs, etc.). Returns: SWIFT/BIC code (if any), name, city, country, institution type, GPI membership, sanctions status across 7 watchlists, and enriched bank profile when available. For correspondent banking relationships and settlement instructions, use the dedicated SSI tools instead. The country parameter accepts both 2-letter ISO codes ("ID", "DE") and full English names ("Indonesia", "Germany"). Names are resolved automatically. Examples: swift_lookup("DEUTDEFF") # exact BIC lookup swift_lookup("Deutsche Bank") # search by name swift_lookup("TBC PAY") # find non-SWIFT payment processor swift_lookup("bank", country="KZ") # explore banks in a country swift_lookup("Halyk", country="KZ") # find specific bank in country swift_lookup("Bank Mandiri", country="Indonesia") # full country name OK
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  • This tool looks up a LOINC code in NLM Clinical Tables and returns guidance on where to obtain a LOINC → SNOMED CT mapping. It does not perform the mapping. Direct LOINC → SNOMED CT mappings are not freely available via API. UMLS Metathesaurus contains the relationships but requires an individual UMLS Terminology Services license; the LOINC SNOMED CT Expression Association is published by Regenstrief Institute as part of the LOINC release and requires authenticated download from loinc.org under the LOINC license. For programmatic LOINC → SNOMED mapping, use UMLS or the LOINC Expression Association files. For interactive lookup, use the SNOMED CT browser available to your organization or the Regenstrief RELMA desktop tool. Provide a LOINC code like "2339-0" (Glucose) or "718-7" (Hemoglobin).
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  • Returns the Origine Paris entity graph: the company and its founders as nodes, with the sourced edges between them (founded, chief executive officer, director, employed by). Use it when you need the relationships between entities; for one entity's own fields use get_brand_identity or get_person_profile instead, not this. Read-only and side-effect-free: it returns structured nodes and edges plus a text copy, every edge carrying its sources, with the index timestamp and the canonical URL, built from Wikidata and corroborated by the site JSON-LD; relationships absent from the sources are not asserted.
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  • Audit the supply chain risk of a GitHub repository's dependencies. Fetches the repo's package.json and/or requirements.txt from GitHub and runs behavioral commitment scoring on every dependency. This is the fastest way to audit a project — just provide the GitHub URL or owner/repo slug, and get a full risk table in seconds. Risk flags: - CRITICAL: single publisher/maintainer/owner + >10M weekly downloads (publish-access concentration risk) - HIGH: sole publisher/maintainer + >1M/wk downloads, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) Examples: - "vercel/next.js" — audit Next.js dependencies - "https://github.com/langchain-ai/langchainjs" — audit LangChain JS - "facebook/react" — audit React's dependency tree - "anthropics/anthropic-sdk-python" — audit Anthropic Python SDK Use this when someone asks "is my project at risk?" or "audit this repo's dependencies".
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  • 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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  • 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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  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • Cloudflare Workers MCP server: code-explainer

  • Get comprehensive RDF data for any entity in the DanNet database. Supports both DanNet entities and external vocabulary entities loaded into the triplestore from various schemas and datasets. UNDERSTANDING THE DATA MODEL: The DanNet database contains entities from multiple sources: - DanNet entities (namespace="dn"): synsets, words, senses, and other resources - External entities (other namespaces): OntoLex vocabulary, Inter-Lingual Index, etc. All entities follow RDF patterns with namespace prefixes for properties and relationships. NAVIGATION TIPS: - DanNet synsets have rich semantic relationships (wn:hypernym, wn:hyponym, etc.) - External entities provide vocabulary definitions and cross-references - Use parse_resource_id() on URI references to get clean IDs - Check @type to understand what kind of entity you're working with Args: identifier: Entity identifier (e.g., "synset-3047", "word-11021628", "LexicalConcept", "i76470") namespace: Namespace for the entity (default: "dn" for DanNet entities) - "dn": DanNet entities via /dannet/data/ endpoint - Other values: External entities via /dannet/external/{namespace}/ endpoint - Common external namespaces: "ontolex", "ili", "wn", "lexinfo", etc. Returns: Dict containing JSON-LD format with: - @context → namespace mappings (if applicable) - @id → entity identifier - @type → entity type - All RDF properties with namespace prefixes (e.g., wn:hypernym, ontolex:evokes) - For DanNet synsets: dns:ontologicalType and dns:sentiment (if applicable) - Entity-specific convenience fields (synset_id, resource_id, etc.) Examples: # DanNet entities get_entity_info("synset-3047") # DanNet synset get_entity_info("word-11021628") # DanNet word get_entity_info("sense-21033604") # DanNet sense # External vocabulary entities get_entity_info("LexicalConcept", namespace="ontolex") # OntoLex class definition get_entity_info("i76470", namespace="ili") # Inter-Lingual Index entry get_entity_info("noun", namespace="lexinfo") # Lexinfo part-of-speech
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  • Get code from a remote public git repository — either a specific function/class by name, a line range, or a full file. PREFERRED WORKFLOW: When search results or findings have already identified a specific function, method, or class, use symbol_name to extract just that declaration. This avoids fetching entire files and keeps context focused. Only fetch full files when you need a broad understanding of a file you haven't seen before. For supported languages (Go, Python, TypeScript, JavaScript, Java, C, C++, C#, Kotlin, Swift, Rust) the response includes a symbols list of declarations with line ranges. This is not a first-call tool — use code_analyze or code_search first to identify targets, then extract precisely what you need.
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  • Get FX trading windows — essential for understanding conversion delays and optimal execution timing. Returns market sessions and liquidity windows for a currency. Use this to understand: - **Delay diagnosis**: Payments arriving outside FX market hours for the target currency are held until the next trading session, adding hours or overnight delays. Critical for restricted currencies (INR, BRL, CNY, etc.). - **Rate optimization**: Higher liquidity = tighter spreads = better rates. Execute during peak windows to minimize conversion costs. Pass a currency code to get its optimal window, or omit to get all market sessions and overlap windows. Args: currency: ISO 4217 currency code (e.g., "EUR", "JPY"). Omit to get all sessions and overlaps. Examples: fx_timing_advisor("EUR") fx_timing_advisor("JPY") fx_timing_advisor("INR") # Check INR conversion windows fx_timing_advisor()
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  • Verify the email code and get a transfer token valid for 15 minutes. Call this after request_transfer_code and the user provides their code. Pass the returned transfer_token to get_transfer_code or unlock_domain. Args: order_id: The order ID of a completed domain purchase. code: The 6-digit code from the verification email.
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  • Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.
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  • Manage the caller's aX identity, memory, and relationships. Use `get` first for a read-only identity card. Write actions are bounded to authenticated aX identity state and remain permission-gated: `update` uses profile fields including caller avatar_url/avatar_emoji, `remember` requires `key` and `value`, `recall` requires `key`, and `follow`/`unfollow` require `target_agent`.
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  • List every error code in the Trillboards API error catalog. WHEN TO USE: - Understanding what error codes the API can return. - Building a client-side error handler that covers all cases. - Looking up error types, HTTP statuses, and documentation URLs. RETURNS: - object: "list" - data: Array of { code, type, http_status, description, doc_url } - total: Total number of error codes. Equivalent to GET /v1/errors but executed in-process (no HTTP round-trip). EXAMPLE: Agent: "What error codes can the API return?" list_error_codes()
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  • Fetch the full dependency tree for a package version including transitive dependencies. Read-only. No side effects. Idempotent. Hard 8-second timeout — large dependency trees may return partial results. package: Package name. Required. version: Exact version string e.g. 1.2.3. Required. ecosystem: One of PyPI, npm, Maven, Go, Cargo, NuGet, RubyGems. Required. Returns all direct and transitive dependencies with version constraints. Use this to understand full supply chain exposure. Use security_fetch_package_vulnerabilities instead when you only need CVEs for a single package. Verified source: deps.dev (Google). 1-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_fetch_dependency_graph", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".
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  • Capture a PNG screenshot of the page or a specific element. Returns base64-encoded image bytes AND a file_id (persisted in DialogBrain files storage). Pass file_id straight to messages.send(attachment_file_ids=[file_id]) — do NOT call files.upload again. Use sparingly — favor browser.snapshot for structured DOM understanding.
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  • Confirm the contact email by entering the 6-digit code the user got in their inbox (v0.18.2). WHEN TO CALL: - publish_need returned error_code = "NEEDS_EMAIL_VERIFICATION", AND the user told you the 6-digit code. WHAT IT DOES: - Verifies the code and marks this connection/account + email as verified. - Subsequent publish_need calls with the same email no longer ask for the code. AFTER CALLING: - Retry the original publish_need with the same i_seek / i_offer / contact.
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  • Work (a composition — the song as written, distinct from any specific recording) by MBID: type, language(s), ISWCs (the work-level standard identifier), writer/composer/lyricist relationships (with the credited artist MBID), aliases, tags, and the recordings that perform it. Recording relations are capped at one page; for the complete list of recordings of a work, call musicbrainz_browse_entities with target_type=recording and link.work.
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  • Get schema details for a Salesforce object (e.g., 'Account'). Returns field names, types, relationships, and metadata. Use before querying to understand available fields.
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  • Show which quality dimensions matter for a stated purpose, WITHOUT ranking any models. Returns the inferred weights and the discovery-walk trace. Useful for understanding how XFMS interprets the purpose before committing to a pick.
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  • Deploys a Cloud Run service directly from local source files. This method is suitable for scripting languages like Python and Node.js, of which the source code can be embedded in the request. This is ideal for quick tests and development feedback loops. You must include all necessary dependencies within the source files because it skips the build step for faster deployment. **Key Requirements:** 1. source_code: Should set to sourceCode.inlinedSource.sources with array of source files, each having `filename` and `content`. 2. Size limit: you are subject to total request size limit of 50MiB.
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