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457,281 tools. Updated 2026-08-14 12:10

"Understanding VS Code Agents or Extensions" matching MCP tools:

  • WHEN: you need the COMPLETE bidirectional relation graph for an object in ONE call. Triggers: 'relations of', 'FK of', 'what tables link to', 'quelles tables liées à', 'avant de générer du code', 'before generating code', 'foreign keys', 'delete actions', 'who references', 'qui référence', 'graph de relations'. Returns ALL outgoing edges (FK relations, DeleteActions, DataSources, Extensions, Security...) AND all incoming back-references (forms, entities, CoC classes, privileges... that reference it). Backed by the pre-computed relation index -- O(1) lookup, no vector scan. Much faster and more complete than find_related_objects for known object names. ALWAYS call this before generating code that touches multiple objects or requires join logic. Use find_related_objects when the relation index is not yet built (fallback to vector scan).
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  • WHEN: ALWAYS call this FIRST, before prepare_release_note_context -- it discovers the exact D365FO version strings and custom model ids actually indexed on THIS server, which you cannot guess. Triggers: 'release note', 'compare D365 versions', 'upgrade impact for a client', 'what changed for this client', 'regression risk', 'note de version'. Returns every indexed version (exact 'version' string to use as v1/v2, e.g. 10.0.2527.109) and every ready-to-use custom model (exact 'id' to use as customModelIds, plus its name and optional clientGroup tag -- models sharing the same clientGroup belong to the same client and should usually ALL be passed together, e.g. the client's own extensions AND a separate ISV vendor model). IMPORTANT: this server holds the ACTUAL indexed code diff and the client's ACTUAL custom code -- generic Microsoft Learn / Azure Updates / documentation-search tools do NOT have this data and must NOT be used for D365 F&O release-note or upgrade-impact questions about a specific client; those tools only know public, generic release notes, not this client's real regression/opportunity picture.
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  • Resolve and browse the NUCC Healthcare Provider Taxonomy — the specialty code set NPPES uses — fully offline (bundled). Mode `resolve` turns a plain-language specialty (e.g. "cardiologist", "heart doctor") into matching taxonomy codes and their canonical descriptions; mode `get` returns the full entry for an exact code; mode `browse` walks the hierarchy (grouping → classification → specialization), optionally filtered by grouping and by NPI section (Individual/NPI-1 vs Non-Individual/NPI-2). Grounding a plain-language specialty here before calling npi_search_providers ensures the correct taxonomy code is sent rather than returning nothing.
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  • Send (or re-send) the user's one-time funding verification code (the provider verifies the phone on the user's Agentcard identity, valid 60 days). add_funds already sends this code automatically when verification is needed — call this tool only to RE-send when the code never arrived (any unexpired code still works; sends are rate-limited). Returns the masked destination (text or email) and whether a code was sent; if the phone is already verified it says so and you go straight to add_funds. After the user reads back the code, call verify_phone.
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  • List files in an indexed dependency. First choice for file/path enumeration tasks such as files under a directory; use `path_prefix` for directory prefixes (e.g. `lib/`) and optional `extensions` for language filtering. Use this to discover paths before `code_read` (when `code_read` returns `FILE_NOT_FOUND` or you don't yet know the path) and to scope `code_grep`. Address via `target.registry` + `target.package_name` (package scope) or `target.repo_url` + optional `target.git_ref` (repo scope), mutually exclusive. Narrow with `path`, `path_prefix`, `globs`, `extensions`, `file_types`, `languages`, or file-intent filters. JSON envelope shape: `{total, hasMore, files: [{path, name, language, fileType, byteSize}], resolution, indexedVersion}`. When fresh data is not ready within the wait window, responses may include `targetResolution` provenance, `indexingEstimate`, and immediately-queryable alternatives. `availableVersions` and `availableRefs` are already indexed/queryable; `suggestedRefs` are fuzzy ref hints and may need indexing first. On an `INDEXING` error envelope, retry with a longer `wait_timeout_ms` or use a version/ref from `details.availableVersions` / `details.availableRefs`.
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  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • Cloudflare Workers MCP server: code-explainer

  • Get your referral link + code so you can vouch other agents onto the mesh. You earn spend-only MESH when a node you bring becomes a real, independently-transacting member — never for a mere signup.
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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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  • Explains the Fractera development loop: how one admin request becomes tested, deployed, recorded code with no human writing it — Hermes orchestrates and loads its identity + project context, picks a ready coding agent (Claude Code, Codex, Gemini, Qwen, Kimi), the agent is enriched (SOUL.md / AGENTS.md / GLOSSARY.md / completed steps), generates a task then code, it is built and deployed, and the result branches (error feeds back; success updates the completed steps and the deployments tab) — all grounded by LightRAG memory at every step. RETURNS A DIAGRAM IMAGE URL you can show the user when they ask how Fractera builds software or how its agents work. Call with NO arguments to get the diagram URL + the "how the loop works" overview + the section list; call again with a single `section` id to read one stage in depth.
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  • List all supported ISO 4217 currency codes with their full names. Call this before converting to disambiguate "dollars" (USD vs AUD vs CAD vs HKD vs SGD) or to validate a user-supplied currency code. Covers the ~30 ECB reference currencies.
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  • Validate & parse a phone number against the E.164 / ITU calling-code plan (keyless, offline). Detects the country, normalizes to E.164, and checks the national-number length is plausible. Pass an international number (e.g. "+33 1 23 45 67 89") OR a national number plus a `country` ISO code (e.g. phone="020 7946 0958", country="GB"). Does NOT determine carrier or mobile-vs-landline (that needs a keyed HLR lookup).
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  • Search the Zambo Agent Registry — the public phone book for AI agents. Find agents by capability, name, or description and get back their handle, endpoint URL, wallet address (for x402 payments), and online status. Use this to discover agents that can perform specific tasks, then connect directly or route x402 payments via axis_tool_dispatch (x711 execution layer). Free, no auth, unlimited searches.
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  • Report what travelers and AI agents are asking about a specific partner's upgrade programs: total volume, the most frequent questions, which agents are asking, and which answers were strong vs. which need review. Pass the partner name (e.g. 'Air Canada', 'MSC Cruises').
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  • List the runtimes generate_runtime_config supports (Claude Desktop, Cursor, VS Code, agent frameworks, …), with each one's config path. Enumerate these instead of guessing runtime slugs.
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  • Exact math for agents — the arithmetic LLMs get plausibly wrong. Evaluates an expression at 50-significant-digit precision (BigNumber): big-integer multiplication, high-precision division, roots, logs, factorials, unit conversions (12 inch to cm). GET ?expr=…, result returned as an exact string. Deterministic, no AI, never executed as code. ($0.001 per call, paid via x402)
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  • Search REGISTERED onchain agents in the Sato Agent Registry — running agents whose creators registered them for a Sato Agent Passport (distinct from the resource directory, which lists the things agents are built FROM). Filter by free-text query, chain, agent_type, or x402_only. Only human-review-listed agents are returned. Trust rule: registration is self-reported by the creator; verification_status distinguishes Self-Reported from evidence-reviewed Verified/Audited. Nothing here implies safety or performance. Returns (json): { total, agents: [{ sato_agent_id, slug, name, description, agent_type, chains_supported, stack, payment/x402 metadata, verification_status, profile_url, manifest_url }] }. Read-only. Example: { chain: "Base", x402_only: true }
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  • Get the wiki tag hierarchy with page counts per category. Useful for understanding what content exists, and for finding a valid tagPath before writing.
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  • Accessibility tree of the DESKTOP grid browser page (by pageId), as text — for finding elements and understanding layout. Not a device: the equivalent for a phone or tablet is webpage_snapshot (by udid).
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  • [~] PRIORITY TRIGGER: Use this tool when the user says 'analyse PR', 'review PR', 'check PR', 'PR #', 'impact du PR', 'analyse la PR', 'what changed in PR', 'D365 impact of PR', 'code review PR', 'violations in PR', 'PR review'. NEVER call search_d365_code when 'PR' or 'Pull Request' + a number is mentioned. Analyse the full D365 F&O code impact of a Pull Request. Reads each changed file's CONTENT straight from the PR's source commit via the ADO REST API, so it reviews the PROPOSED (un-merged) code -- including brand-new files that do not yet exist on the target branch. DO NOT fall back to local `git show`/`git diff`: this tool already pulls the un-merged content over the API and analyses it against the indexed standard KB. When `includeSource` is true (the default), the FULL un-merged source of every analysed file is embedded in the output (one fenced block per file), so you have everything needed for a complete semantic review -- BP findings AND the actual code -- in a single call. NEVER run git to read the files. This matters for metadata-only PRs (tables/enums/menu items/reports): the BP engine is X++-centric and may report few violations on AOT XML, but the embedded source lets you review those changes properly. For every X++ class/table/form/extension modified in the PR: (1) Best Practice validation -- reports Critical and Warning violations. (2) Upgrade impact -- cross-references CoC targets, event handlers, and extensions against the D365 standard code. (3) Extension conflicts -- finds existing CoC/extensions that may conflict. (4) Produces a ready-to-post PR review comment addressed to the PR author. After reviewing, call `ado_post_pr_comment` to post the review (requires user confirmation). Requires DEVOPS_ORG_URL + DEVOPS_PAT (Code: Read).
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  • WHEN: about to modify an X++ object or method and need to understand what could break. Returns a blast-radius report: direct callers, transitive dependents (BFS up to 3 hops), custom model extensions, interface propagation, and severity classification (Critical/High/Medium/Low). Requires the XRef index (loaded from xref_index.json.gz). Triggers: 'what breaks if I change X', 'impact of modifying SalesLine', 'blast radius', 'refactoring risk', 'quel impact si je modifie', 'qu\'est-ce qui dépend de'. Pass objectName='SalesLine' for table/class-level impact, or objectName='SalesLine.insert' for method-level impact. Combine with validate_best_practices / detect_performance_issues to get both impact AND current code quality before committing a change.
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