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634,819 tools. Updated 2026-10-03 21:02

"Understanding Gaode Map MCP" matching MCP tools:

  • One call, pick your field groups — resolves a slug OR any identifier and returns exactly the groups you ask for, instead of chaining get_provider + get_provider_rating + get_provider_artifacts + get_provider_onboarding. Groups: profile, onboarding, artifacts, rating, insights. Understanding plan — the base groups moved with the rest of the discovery layer on 2026-08-31. Priced B2 (cross-catalog synthesis) — $0.05 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.
    ConnectorNo auth
  • WHAT: Firmensitz / registered office once (SITE.geo = Adalbert-Stifter-Str. 14, 71638 Ludwigsburg). RETURNS: street, postal, city, lat/lng, icbm, walkIn=false, firmensitz_url=https://maps.ikeytz.com/buero, embed_map=same, embed_map_compact=?embed=1, geo_api=/api/v1/embed/office, google_business=GBP share (external click only). canonicalUrl = firmensitz map. NOT a shop — never send customers to walk in. NOT a service-area place map (use list_service_areas / get_service_area for Ort slugs). NEXT: get_contact, get_legal(doc=impressum), or maps MCP get_geo_office on maps.ikeytz.com/mcp.
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  • Token-efficient repo (or subtree) skeleton: directory tree with each file's classes (methods in parens), functions, and HTTP endpoints, from the graph. Orient before drilling in. Scope with "path", cap with "maxDepth", density:"full" adds properties. view:"architecture" instead returns a module map (Louvain clusters with hubs, paths and cross-module coupling), plus namedModules/totalModules: a module NAME comes from a generated summary and is provisional, its id (the member-set hash in the header) is the stable key, so pin modules by id and re-read names rather than caching them.
    ConnectorNo auth
  • Who on the team is actually using the Coderbuds MCP. Every MCP tool call is recorded per member, so this reports adoption over a recent window (default 30 days): total invocations, per-member usage with last-used time and favourite tool, per-tool call counts, and — the nudge list — login members who have never connected the MCP at all. The denominator is who could plausibly connect one today — a login member (only they can mint API tokens) who is still shipping code. Tracked contributors cannot connect, deactivated or long-inactive members have left, and someone with several linked identities counts once. Use when asked "who is using the MCP", "is the team on the MCP yet", or to find who still needs the setup instructions. A call is attributed to the team it was about — the `repository` slug on it, or the `?team=` binding on the connection — not to whichever team the web switcher last landed on, so a member working across several teams shows up under the one they were working in.
    ConnectorOAuth
  • Get price statistics aggregated by postal code or commune zones — returns JSON data suitable as input for heatmap visualizations (not a rendered map or image). Hosts with MCP Apps support additionally render this as an interactive bubble map. REQUIRED: At least one scope filter: - code_departement: Department code (e.g., "75" for Paris) - commune: Major city (e.g., "PARIS" - returns all arrondissements) Optional: - type_local: "Maison" or "Appartement" - group_by: "code_postal" (default) or "commune" - min_transactions: Minimum transactions to include zone (default: 10) - date_debut/date_fin: Date range (default: last year) Returns per zone: - Centroid coordinates (lat/lon) for map plotting - Median and average price/m² - Transaction count - Relative position: "expensive", "average", or "affordable" Use this when you need to: compare price levels across an entire department, find the most/least expensive zones, or provide data to build a price heatmap. Do NOT call this expecting a rendered image — it returns structured JSON data only. Example: Paris zones by postal code: {commune: "PARIS", type_local: "Appartement"} Cost: 15 credits per call
    ConnectorAPI key
  • [Tier 2 — Direct Build intake] When: you have part-to-territory assignment rows or a legacy spreadsheet (e.g. Zip2Terr.csv with Postal Code + Territory/Region/Division) that you cannot inline in direct_build. Stage rows here, then call direct_build(assignments_handle=<upload_handle>). FOUR WAYS TO STAGE (all return upload_handle): (A) MCP csv_file: pass the uploaded CSV as a ChatGPT/OpenAI file parameter. (B) MCP csv_text: pass csv_text=<raw multiline CSV> — preserve newlines; do NOT JSON-encode with PowerShell ConvertTo-Json (corrupts rows). (C) MCP assignments: pass assignments=<chunk of row objects>; append with upload_handle. (D) HTTP POST /assignments/upload with assignments, csv_text, or csv_file. Legacy columns (Postal Code, Territory, Region, Division) auto-map to part_id + territory_path. Then: direct_build(assignments_handle=<handle>, part_layer=..., tal_label=..., map_session_id=...). Handle is single-use and expires (default 1h).
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    Provides a structured map of 120 practical AI prompts across 6 business domains, enabling users to quickly generate complete prompts for specific tasks using slash commands or tools.
    2
    8 npm
    MIT

Matching MCP Connectors

  • [Tier 2 — MCP Tasks mirror] Tool-only client equivalent of native tasks/result. Call exactly once after tasks_get returns status=completed and _meta.next_action=consume_result. Prerequisite: task_id from that completed Task. Returns the originating tool's terminal handle-only result (ts_handle, counts, timings, map binding/shortcut); it never returns inline TS when a handle exists. Do not poll this operation while working. After build results, pass ts_handle or the same task_id as job_id to analyze with explicit tal_ids; never resubmit a build to recover from an Analyze lookup error.
    ConnectorNo auth
  • Returns a machine-readable routing map for Spala MCP clients. Identifies public and authenticated tools, supported installer clients, OAuth endpoints, project handoff rules, and project-MCP entry points.
    ConnectorNo auth
  • Returns the complete Trident 2D specification including grammar, syntax rules, coordinate system, containers, nodes, connections, shapes, and icon reference. Use this when you need deep understanding of the Trident DSL.
    ConnectorNo auth
  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
    ConnectorNo auth
  • 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.
    ConnectorNo auth
  • Simulate int8 or int4 quantization of float32 embedding vectors. Reduces storage by 4x (int8) or 8x (int4). Returns quantized values, scale factor, and precision loss (MSE). Useful for understanding vector DB compression trade-offs.
    ConnectorNo auth
  • Check subscription status, plan details, billing cycle, and feature access. Useful for understanding what the business can and cannot do on their current plan.
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  • Optional wallet login/register step 3 (not required if the agent already has an API key). Pass challenge + wallet signature from steps 1–2. isNewUser=true -> POST /api/registerUser; else POST /api/logon. On success, map body.requestToken/requestSecret to X-MBX-APIKEY / X-MBX-APISECRET; use body.id as account. Wallet signing stays outside MCP.
    ConnectorNo auth
  • Browse all funding categories with opportunity counts. Categories include: Grant, Construction, Goods & Services, Professional Services, Technology, Healthcare, Research, and more. Useful for understanding what types of opportunities are available. Does not count toward your monthly searches.
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  • EXPLORE — the agent-readiness dimensions and standalone score for ONE provider (spec presence, MCP server, auth clarity, idempotency, error semantics, rate-limit signal, well-known catalog, consent identity, dry-run…). A STANDALONE score, not a slice of the composite. For the same question across the catalog — who is agent-ready, which dimensions have actually diffused — use find_agent_readiness (Influence). Priced B1 (single-entity synthesis) — $0.01 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.
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  • UNDERSTANDING — the agent-readiness leaderboard across the whole catalog. Rank providers by agent readiness, and filter to those that DO satisfy (has) or do NOT satisfy (missing) specific dimensions — e.g. has="mcp_server,protected_resource_metadata" is the OAuth-capable MCP cohort, missing="agent_card" is the addressable market for a fix. Returns agent score + band alongside the Kin Score. Priced per result — $0.005 per request plus $0.0002 per record returned (less past 100), capped at $0.50 a request, under pay-as-you-go; included in Understanding and Influence. Estimate first at /api/v1/prices/estimate. See apis://prices.
    ConnectorNo auth
  • WHEN: mapping the technical D365 objects behind a business process, or understanding which tables/forms implement a flow. Triggers: 'processus métier', 'Order-to-Cash', 'Procure-to-Pay', 'Record-to-Report', 'business process flow', 'qui est impliqué dans', 'map the process', 'flux du processus', 'quels objets dans le flux'. Map a D365 F&O business process to its complete object chain. For known processes (Order-to-Cash, Procure-to-Pay, Record-to-Report, Plan-to-Produce, Inventory-Management, Hire-to-Retire, Project-Accounting, Asset-Lifecycle): shows every step with forms, tables, classes, entities, reports, and security roles involved. For any other object name: traces all dependencies (tables, classes, forms, entities) from that entry point. Produces a Mermaid process flow diagram. Use 'list' to see all known process mappings. NOT for a single object's FK relations only -- use `find_related_objects` for that (faster and more precise).
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  • Look up one map: title, regionType, regionCount, labels, layers, and its regions as {key, title}, 200 per page. You rarely need this before rendering. render_map accepts region names, codes and common aliases and auto-corrects typos, reporting what it matched. Use it to build a dataset covering every region of a map, to see how a map names its regions, or to resolve a key render_map could not match. `query` searches keys, titles and aliases, so no hits means the map really has no such region. Use `offset` for further pages.
    ConnectorNo auth
  • Look up one map: title, regionType, regionCount, labels, layers, and its regions as {key, title}, 200 per page. You rarely need this before rendering. render_map accepts region names, codes and common aliases and auto-corrects typos, reporting what it matched. Use it to build a dataset covering every region of a map, to see how a map names its regions, or to resolve a key render_map could not match. `query` searches keys, titles and aliases, so no hits means the map really has no such region. Use `offset` for further pages.
    ConnectorNo auth
  • 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).
    ConnectorOAuth