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161,477 tools. Last updated 2026-05-30 03:25
"How to interact with Google Maps using Python" matching MCP tools:
- Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.Connector
- Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.Connector
- Repay debt to an Arcadia lending pool using tokens from the wallet (requires ERC20 allowance). To repay using account collateral instead (no wallet tokens needed), use write_account_deleverage. Check allowance first (read_wallet_allowances), then approve the pool if needed (write_wallet_approve). Check outstanding debt with read_account_info.Connector
- Lists directly accessible Google Ads customers for the configured Google Ads credentials, including descriptive names when Google returns them. Use this to discover customer IDs before running Google Ads hierarchy or reporting tools.Connector
- Returns the calling account's id/email/role plus internal-use eligibility: whether the account is staff-flagged, which domains run free, and how a given target URL would be billed if you submitted a test now. Use this first when you bring TMV into a new project — it confirms the project's API key actually maps to the expected operator account.Connector
Matching MCP Servers
- AlicenseAqualityCmaintenanceProvides access to Google Maps API functionality including places search, geocoding, directions, distance matrix, elevation data, and static map generation through the MCP interface.Last updated863MIT
- Alicense-qualityCmaintenanceProvides access to Google Maps functionality including places search, geocoding, directions, distance calculations, elevation data, and static map generation through the Model Context Protocol interface.Last updated684MIT
Matching MCP Connectors
The Google Maps MCP server is a fully-managed server provided by the Maps Grounding Lite API that connects AI applications to Google Maps Platform services. It provides three main tools for building LLM applications: searching for places, looking up weather information, and computing routes with details like distance and travel time. The server acts as a proxy that translates Google Maps data into a format that AI applications can understand, enabling agents to accurately answer real-world location and travel queries.
Local business lead extraction with email + phone enrichment from Google Maps.
- Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.Connector
- Search for verified local service providers across 9 trade categories: floor coating (epoxy/polyaspartic), radon mitigation, crawl space repair, laundry pickup & delivery, mold/asbestos abatement, basement waterproofing, foundation/slab repair, septic pump services, and water damage restoration. Returns provider name, rating, review count, business status, services offered, certifications, years in business, and a link to the full profile with contact details. Each provider includes Google Maps URL when available. Covers major US metro areas. Use list_niches first to get valid niche IDs, and list_service_types for valid service_type values.Connector
- # Instructions 1. Query OpenTelemetry metrics stored in Axiom using MPL (Metrics Processing Language). NOT APL. 2. The query targets a metrics dataset (kind "otel-metrics-v1"). 3. Use listMetrics() to discover available metric names in a dataset before querying. 4. Use listMetricTags() and getMetricTagValues() to discover filtering dimensions. 5. ALWAYS restrict the time range to the smallest possible range that meets your needs. 6. NEVER guess metric names or tag values. Always discover them first. # MPL Query Syntax A query has three parts: source, filtering, and transformation. Filters must appear before transformations. ## Source ``` <dataset>:<metric> ``` Backtick-escape identifiers containing special characters: ``my-dataset``:``http.server.duration`` ## Filtering (where) Chain filters with `|`. Use `where` (not `filter`, which is deprecated). ``` | where <tag> <op> <value> ``` Operators: ==, !=, >, <, >=, <= Values: "string", 42, 42.0, true, /regexp/ Combine with: and, or, not, parentheses ## Transformations ### Aggregation (align) — aggregate data over time windows ``` | align to <interval> using <function> ``` Functions: avg, sum, min, max, count, last Intervals: 5m, 1h, 1d, etc. ### Grouping (group) — group series by tags ``` | group by <tag1>, <tag2> using <function> ``` Functions: avg, sum, min, max, count Without `by`: combines all series: `| group using sum` ### Mapping (map) — transform values in place ``` | map rate // per-second rate of change | map increase // increase between datapoints | map + 5 // arithmetic: +, -, *, / | map abs // absolute value | map fill::prev // fill gaps with previous value | map fill::const(0) // fill gaps with constant | map filter::lt(0.4) // remove datapoints >= 0.4 | map filter::gt(100) // remove datapoints <= 100 | map is::gte(0.5) // set to 1.0 if >= 0.5, else 0.0 ``` ### Computation (compute) — combine two metrics ``` ( `dataset`:`errors_total` | group using sum, `dataset`:`requests_total` | group using sum; ) | compute error_rate using / ``` Functions: +, -, *, /, min, max, avg ### Bucketing (bucket) — for histograms ``` | bucket by method, path to 5m using histogram(count, 0.5, 0.9, 0.99) | bucket by method to 5m using interpolate_delta_histogram(0.90, 0.99) | bucket by method to 5m using interpolate_cumulative_histogram(rate, 0.90, 0.99) ``` ### Prometheus compatibility ``` | align to 5m using prom::rate // Prometheus-style rate ``` ## Identifiers Use backticks for names with special characters: ``my-dataset``, ``service.name``, ``http.request.duration`` # Examples Basic query: `my-metrics`:`http.server.duration` | align to 5m using avg Filtered: `my-metrics`:`http.server.duration` | where `service.name` == "frontend" | align to 5m using avg Grouped: `my-metrics`:`http.server.duration` | align to 5m using avg | group by endpoint using sum Rate: `my-metrics`:`http.requests.total` | align to 5m using prom::rate | group by method, path, code using sum Error rate (compute): ( `my-metrics`:`http.requests.total` | where code >= 400 | group by method, path using sum, `my-metrics`:`http.requests.total` | group by method, path using sum; ) | compute error_rate using / | align to 5m using avg SLI (error budget): ( `my-metrics`:`http.requests.total` | where code >= 500 | align to 1h using prom::rate | group using sum, `my-metrics`:`http.requests.total` | align to 1h using prom::rate | group using sum; ) | compute error_rate using / | map is::lt(0.2) | align to 7d using avg Histogram percentiles: `my-metrics`:`http.request.duration.seconds.bucket` | bucket by method, path to 5m using interpolate_delta_histogram(0.90, 0.99) Fill gaps: `my-metrics`:`cpu.usage` | map fill::prev | align to 1m using avgConnector
- Get full details + ready-to-paste call template for a service. Returns the service row plus a `call_template` field: - call_template.mcp : how to call via MCP streamable-http (python snippet, inspector CLI line, Claude Desktop config fragment). - call_template.http_x402 : 5-step HTTP+402 payment flow with the exact endpoint URL and a curl probe. Use this AFTER `search` to grab the snippet — no need for the agent to hand-craft an x402 client. Args: slug: Service slug as returned by `search` items.Connector
- Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.Connector
- Explain the Guard product using CurrencyGuard's approved product and FAQ content. Covers: what the Guard is, how it works, who it is for, how it compares to forwards or options, and legal, regulatory, accounting, or eligibility questions.Connector
- Resolves a list of Google Maps URLs into canonical Google Maps Place IDs. **When to call this tool (CRITICAL):** * Use this tool when the user provides one or more Google Maps sharing links or URLs (e.g. 'https://maps.app.goo.gl/...', 'https://www.google.com/maps/place/...', or 'https://maps.google.com/...') and you need to extract the underlying canonical Place IDs. * You can specify up to 20 URLs to resolve in a single batch request. **Input Requirements (CRITICAL):** * **`urls` (array of strings - MANDATORY):** The list of Google Maps URLs to resolve. Each URL must be a valid, single-place Google Maps URL. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some URLs resolve successfully while others fail). * The output list of `entities` is guaranteed to map 1:1 with the input `urls` indices. A failed URL resolution will result in an empty `Entity` message (no fields are set) at its corresponding index in the `entities` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific URL index failed. The key of `failed_requests` represents the 0-based index of the failed URL in the request. Do not assume the entire batch call failed because of a partial failure.Connector
- Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo, stewardship, information, full_pipeline (aliases accepted: init, config, ingest, remove, search, redoer, force_resolve, info, e2e). V3 supports Python and Java only. Returns GitHub raw URLs — fetch each snippet to read the source code.Connector
- Get Place Photos Fetches the photo gallery of a Google Maps place by dataId or placeId, paginated with nextPageToken and filterable by categoryId (all, latest, menu, by owner, videos, street view). Returns each photo with image URL, thumbnail, upload date, uploader, and photoId. Use for restaurant-menu extraction, venue/ambience visual audits, building rich place detail pages, and sourcing up-to-date imagery for POI listings.Connector
- Resolves a list of Google Maps URLs into canonical Google Maps Place IDs. **When to call this tool (CRITICAL):** * Use this tool when the user provides one or more Google Maps sharing links or URLs (e.g. 'https://maps.app.goo.gl/...', 'https://www.google.com/maps/place/...', or 'https://maps.google.com/...') and you need to extract the underlying canonical Place IDs. * You can specify up to 20 URLs to resolve in a single batch request. **Input Requirements (CRITICAL):** * **`urls` (array of strings - MANDATORY):** The list of Google Maps URLs to resolve. Each URL must be a valid, single-place Google Maps URL. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some URLs resolve successfully while others fail). * The output list of `entities` is guaranteed to map 1:1 with the input `urls` indices. A failed URL resolution will result in an empty `Entity` message (no fields are set) at its corresponding index in the `entities` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific URL index failed. The key of `failed_requests` represents the 0-based index of the failed URL in the request. Do not assume the entire batch call failed because of a partial failure.Connector
- Get Immersive Product Information Expands the Google Shopping Immersive Product pop-up given an immersiveProductPageToken from the Google Shopping API, with optional moreStores (up to ~13 merchants instead of 3–5) and nextPageToken for paginating stores. Returns multi-store offers (merchant, price, shipping, condition, URL), product specs, images, ratings, and the nextPageToken. Use for price-comparison bots, merchant discovery, dropshipping research, and aggregating full offer lists per product.Connector
- Render a mingrammer/diagrams Python snippet to PNG and return the image. The code must be a complete Python script using `from diagrams import ...` imports and a `with Diagram(...)` context manager block. Use search_nodes to verify node names and get correct import paths before writing code. Read the diagrams://reference/diagram, diagrams://reference/edge, and diagrams://reference/cluster resources for constructor options and usage examples. Args: code: Full Python code using the diagrams library. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.Connector
- Use this as the primary tool to retrieve a single specific custom monitoring dashboard from a Google Cloud project using the resource name of the requested dashboard. Custom monitoring dashboards let users view and analyze data from different sources in the same context. This is often used as a follow on to list_dashboards to get full details on a specific dashboard.Connector
- Is it safe to deploy these changes? Cross-references your changed modules against active constraints, recent incidents, knowledge freshness, and active alerts. Returns a composite verdict (ready/caution/block) with per-module breakdown and actionable recommendations. Use BEFORE deploying to catch constraint violations, recent regressions in the same area, stale knowledge that needs verification, and active alerts that might interact with your changes.Connector