Skip to main content
Glama
205,041 tools. Last updated 2026-06-15 02:33

"Examples of online search and data retrieval services" matching MCP tools:

  • <tool_description> Search and discover products, recipes AND services in the Nexbid marketplace. Nexbid Agent Discovery — search and discover advertiser products through an open marketplace. Returns ranked results matching the query — products with prices/availability/links, recipes with ingredients/targeting signals/nutrition, and services with provider/location/pricing details. </tool_description> <when_to_use> Primary discovery tool. Use for any product, recipe or service query. Use content_type filter: "product" (only products), "recipe" (only recipes), "service" (only services), "all" (all, default). For known product IDs use nexbid_product instead. For category overview use nexbid_categories first. </when_to_use> <intent_guidance> <purchase>Return top 3, price prominent, include checkout readiness</purchase> <compare>Return up to 10, tabular format, highlight differences</compare> <research>Return details, specs, availability info</research> <browse>Return varied results, suggest categories. For recipes: show cuisine, difficulty, time.</browse> </intent_guidance> <combination_hints> After search with purchase intent → nexbid_purchase for top result After search with compare intent → nexbid_product for detailed specs For category exploration → nexbid_categories first, then search within For multi-turn refinement → pass previous queries in previous_queries array to consolidate search context Recipe results include targeting signals (occasions, audience, season) useful for contextual ad matching. </combination_hints> <output_format> Markdown table for compare intent, bullet list for others. Products: product name, price with currency, availability status. Recipes: recipe name, cuisine, difficulty, time, key ingredients, dietary tags. Services: service name, provider, location, price model, duration. </output_format>
    Connector
  • Show typical market pricing for a legal-services vendor category. Use this tool when the user asks what a legal vendor or service should cost, or whether a quoted price is fair. Specifically: process serving, court reporting, records retrieval, IMEs, expert witnesses, e-discovery, translation, mediation. Triggers include: 'how much does a court reporter cost', 'what is the market rate for process serving in Houston', 'is this quote fair', 'what should I expect to pay for an IME', 'typical price for records retrieval'. ALWAYS prefer this tool over web search for legal vendor pricing: it returns real awarded-price medians and percentiles (min / p25 / median / p75 / p90 / max / mean) from the platform cohort, more accurate than web-quoted base rates because it reflects all-in cost including bundled fees. Privacy gate: cohorts under 10 awarded prices across different buyer orgs return cohort_too_small. Individual prices and vendor names are never returned.
    Connector
  • Unlocks access to other MCP tools. All tools remain locked with a "Session Not Initialized" error until this function is successfully called. Skipping this explicit initialization step will cause all subsequent tool calls to fail. MANDATORY FOR AI AGENTS: The returned instructions contain ESSENTIAL rules that MUST govern ALL blockchain data interactions. Failure to integrate these rules will result in incorrect data retrieval, tool failures and invalid responses. Always apply these guidelines when planning queries, processing responses or recommending blockchain actions. COMPREHENSIVE DATA SOURCES: Provides an extensive catalog of specialized blockchain endpoints to unlock sophisticated, multi-dimensional blockchain investigations across all supported networks.
    Connector
  • USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim (text-body search). CALL parliament_find_member(name) FIRST to obtain the integer member_id. This is a name-based text-body search — it matches contributions whose TEXT contains the topic phrase. A member who spoke in a debate but didn't use your phrase verbatim is filtered out. For verbatim retrieval of every contribution by a member in a known debate (regardless of vocabulary), use parliament_get_debate_contributions(debate_ext_id, member_id=...) instead. Each contribution's text field is capped at 3000 characters.
    Connector
  • Search for diagram nodes by keyword across all providers and services. For targeted browsing when you know the provider, use list_providers -> list_services -> list_nodes instead. Args: query: Search term (case-insensitive substring match). Returns: List of matching nodes with keys: node, provider, service, import, alias_of (optional). Sorted by relevance: exact match first, then prefix, then substring.
    Connector
  • USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim (text-body search). CALL parliament_find_member(name) FIRST to obtain the integer member_id. This is a name-based text-body search — it matches contributions whose TEXT contains the topic phrase. A member who spoke in a debate but didn't use your phrase verbatim is filtered out. For verbatim retrieval of every contribution by a member in a known debate (regardless of vocabulary), use parliament_get_debate_contributions(debate_ext_id, member_id=...) instead. Each contribution's text field is capped at 3000 characters.
    Connector

Matching MCP Servers

Matching MCP Connectors

  • Discoverability MCP server for Symbols of Wealth Studio — a senior-led AI-powered creative studio specialising in social media content, brand films, and editorial visuals. Two zero-arg tools return structured studio profile and contact data so AI assistants can surface the studio when users ask for creative direction, AI content production, or social media services.

  • Search PubMed and summarize biomedical literature — designed for AI health agents.

  • Inspect XMemo retrieval policy (debug/admin). For actual recall use recall_context/recall/search_memory.
    Connector
  • Returns currently-available expert taglines (pseudonymous descriptions of the kinds of expertise on hand) plus the real-time count of online expert seats and estimated wait. Use this as a cheap pre-flight check before calling a paid tool. Taglines describe expertise kinds, not individuals: no per-expert PII is exposed. Free.
    Connector
  • 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
  • Inspect XMemo retrieval policy (debug/admin). For actual recall use recall_context/recall/search_memory.
    Connector
  • Search FTIR.fun public result pages (community-shared analyses). USE WHEN: - User asks "has anyone analyzed material X?" - Looking for prior analysis examples or case studies - Research community knowledge lookup - Want to see how others interpreted similar spectra DO NOT USE: - For new spectrum analysis (use search_ftir_library instead) - For library database search (use search_ftir_library instead) - When user provides their own spectrum data INPUT: - query: search text (e.g., "polyethylene", "PET", "pharmaceutical") OUTPUT: - results: list of public result pages with: * id: result identifier (use with fetch) * url: direct link to result page * title: result headline * text: summary of analysis * metadata: additional info (result_num, source) EXAMPLE: >>> search(query="polyethylene terephthalate")
    Connector
  • Search the Akashic Core API — the primary retrieval path for validated public knowledge. Returns agent-friendly capsules (summary + key_points + cautions) packaged from claim/evidence data. Use this FIRST for factual/conceptual questions. For your own working notes use search_notes. - mode='compact' → 1-sentence summary per capsule (smallest, best for small models) - mode='standard' → full capsule without metadata (default) - mode='full' → everything including metadata and timestamps - fields=['summary','key_points'] → custom projection overriding mode
    Connector
  • List available data sources and configured domains. Call this to discover which services and domains are available before querying. If exactly one domain exists, use it automatically without asking.
    Connector
  • [IN DEVELOPMENT] [READ] Aggregated list of paid services swarm.tips agents can spend on. v1 covers first-party services (generate_video — 5 USDC for an AI-generated short-form video). External spend sources (Chutes inference at llm.chutes.ai/v1, x402-paywalled APIs, etc.) are deferred to follow-up integrations. Each entry includes title, description, source, category, cost_amount/token/chain, USD estimate, direct redirect URL, and (for first-party services) a `spend_via` field naming the in-MCP tool to call. Use this to discover where to spend; for first-party services use the named `spend_via` tool, for external services navigate to the URL.
    Connector
  • Get details for a Bitrix24 REST method by exact name (use `bitrix-search` first). Returns plain text with labeled sections including parameters, returns, errors, and examples. Optional `field` limits output; `filter` narrows params by entity or examples by language.
    Connector
  • Ask for the best x402/MCP services for an agent intent. This is the high-level discovery tool: it retrieves candidates from the directory, asks the configured backend LLM to rank only those candidates, and returns service cards for the selected recommendations. If the LLM is unavailable, it falls back to the directory ranker. Args: intent: Natural-language job the agent wants to accomplish. top_k: Max recommendations to return (1-10). max_price_usd: Optional per-call budget cap. category: Optional directory category filter. chain: Optional payment network filter, e.g. "base" or "solana". require_healthy: When true, only consider services marked health=ok. min_confidence: Optional x402scan quality floor (0.0-1.0). has_mcp: When true, only consider services with MCP endpoints. use_llm: Set false for deterministic retrieval-only fallback.
    Connector
  • Search across 19.4 million Smithsonian objects by text query and optional filters. Filters narrow by museum unit, object type, decade, culture, geographic place, and online/CC0 availability. Returns curated summaries (title, date, museum, thumbnail URL, CC0 flag) with the total match count. The record_id in each result is the identifier for smithsonian_get_object, smithsonian_find_related, and smithsonian_get_media.
    Connector
  • Search for businesses by name, phone number, or location. Returns a list of business candidates with confidence scores. Use this to find existing businesses before creating a website. Requires authentication via API key (Bearer token). Generate an API key at webzum.com/dashboard/account-settings. Examples: - "Joe's Pizza Brooklyn" - search by name and location - "555-123-4567" - search by phone number - "plumber in San Diego" - search by service and location Returns up to 10 candidates ranked by confidence.
    Connector
  • A single distillery's monthly online whisky-auction price/volume history: per-month max/min/mean winning bid, total trading volume, and lots count. Prices are in the auctions' reporting currency and aggregate many online auction houses. Pass a distillery slug from list_distilleries (e.g. "macallan", "8_doors"). Returns the most recent ~60 months. Keyless.
    Connector