"How to search for Facebook profiles" matching MCP tools:

• search_content

  mental-health-care

  Search the Emora Health editorial corpus by article title. Returns up to 20 articles per page with title, description, URL, and category. ALWAYS USE THIS for information questions ("tell me about X", "what are signs of Y", "how does Z work"). Do not answer from training data when this tool can return clinician-reviewed content.

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• search_community

  Heista

  Community-discourse search via parallel.ai with optional platform filtering. Returns synthesized text excerpts plus direct URLs to real Reddit threads, X posts from named operators, Substack essays, LinkedIn posts, Facebook posts. Use for: "what are practitioners saying about X", recurring themes in founder voice, multi-platform discourse mapping, verbatim quotes from named individuals. Per Phase 3.5 empirical A/B (Docs/solutions/architecture-decisions/search-backend-architecture-jun04.md): this tool SOLVES the Reddit/X retrieval gap that perplexity_search fundamentally couldn't fill. Optional platforms[] to restrict (e.g. ["reddit","x","substack"]). Per social-listening-synthesis §3 sample ≥3 platforms per brief.

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• match_creators

  Influship

  Score how well specific creators fit a campaign brief or search intent. Use this when the user already has candidate creators in mind and wants to evaluate fit (e.g., "rate these 5 creators for a vegan cookbook launch", "which of these is the best match for my crypto audience?"). For each creator the API returns a match score (0-1), a good/neutral/avoid decision, and structured reasons. Pass candidates in `creator_ids` (canonical UUIDs) and/or `profiles` (platform + username). `intent_query` is the brief the LLM reasons against; `intent_context` is optional extra context (target audience, brand values, prior collabs). Use `semantic_search_creators` when you don't have candidates yet and need topical or niche discovery. Use `search_creators` first when you only need to resolve rough creator names/handles into candidates. Use `find_lookalike_creators` when you want creators similar to known good fits. Examples: - User: "Is @niickjackson a fit for Pixel?" -> use this tool after resolving the exact Instagram profile with `get_profile`; call `get_posts` first if recent content context is needed. - User: "Rate these five creators for a vegan cookbook launch" -> use this tool.

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• estimate_market

  Ground Truth - First Tool Call

  Search npm or PyPI to estimate how crowded a package category is before you claim that a market is empty, niche, or competitive. Use this when you have a category or search phrase such as 'edge orm' and want live result counts plus representative matches. Do not use it to compare exact known package names or to infer adoption from downloads; it reflects search results, not market share. Registry responses are cached for 5 minutes.

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• searchCollaborators

  qubitsok — Quantum Computing Jobs, Papers & Researchers

  Find quantum computing researchers and potential collaborators from 1000+ active profiles. Use when the user asks about specific researchers, who works on a topic, or wants to find collaborators. NOT for jobs (use searchJobs) or papers (use searchPapers). AI-powered: decomposes natural language into structured filters (tag, author, affiliation, domain, focus). Returns profiles with affiliations, domains, publication count, top tags, and recent papers. Data from arXiv papers published in the last 12 months. Max 50 results. Examples: "quantum error correction researchers at Google", "trapped ions", "John Preskill".

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• knowledge_query

  dialogbrain

  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.

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• bsky_search_actors

  bluesky-mcp-server

  Find Bluesky accounts by name or handle fragment. Returns ranked profiles with handle, DID, displayName, bio, and follower count. Use before bsky_get_profile or bsky_get_author_feed when you have a name but not a confirmed handle. Supports cursor-based pagination for browsing beyond the first page of results.

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• fema_search_disasters

  fema-mcp-server

  Search federal disaster declarations by state, incident type, declaration type, date range, and county. Returns deduplicated declaration-level summaries — each disaster number appears once with a designatedAreaCount showing how many counties/municipalities were designated. The disaster number is the chain key for fema_get_disaster, fema_get_public_assistance, and fema_get_housing_assistance. Use declaration_type to filter: DR (major disaster, most common), EM (emergency), FM (fire management). Date filters apply to the declaration date. Use fema_get_disaster to retrieve all designated-area rows for a specific declaration.

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• semantic_search_creators

  Influship

  Semantic discovery search for influencers/content creators using natural-language queries. Use this only when the user asks to discover creators by topic, audience, geography, niche, content style, or campaign criteria (e.g., "fitness creators in NYC", "vegan recipe creators with high engagement", "tech reviewers who cover phones"). The query is matched against creator profiles, extracted facts, and visual style via hybrid vector search. Do not use this for exact handles, usernames, or known creator names. If the user gives a specific platform and handle (for example "@niickjackson on Instagram"), use `get_profile` first. For rough name/handle lookup, use `search_creators`. For multiple known handles, use `lookup_profiles`. Semantic search can return lookalike or topical matches and is allowed to miss an exact username. Examples: - User: "Find news creators with 1M+ followers" -> use this tool. - User: "Find creators in LA who make cinematic travel videos" -> use this tool. - User: "Pull @niickjackson on Instagram" -> use `get_profile`, not this tool. - User: "Is @niickjackson a fit for Pixel?" -> use `get_profile` first, optionally `get_posts`, then `match_creators`. Returns a ranked list of creators (id, platform, username, follower count, engagement rate, top categories, evidence facts). Use the flat follower, engagement-rate, and verified fields to constrain results when the user gives concrete numeric constraints. Use `find_lookalike_creators` instead when you want creators SIMILAR to known ones. Use `match_creators` when you want to SCORE specific creators against a brief.

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• search_humans

  Human Pages

  Search for humans available for hire. Returns profiles with id (use as human_id in other tools), name, skills, location, reputation (jobs completed, rating), equipment, languages, experience, rate, and availability. All filters are optional — combine any or use none to browse. Key filters: skill (e.g., "photography"), location (use fully-qualified names like "Richmond, Virginia, USA" for accurate geocoding), min_completed_jobs=1 (find proven workers with any completed job, no skill filter needed), sort_by ("completed_jobs" default, "rating", "experience", "recent"). Default search radius is 30km. Response includes total count and resolvedLocation. Contact info requires get_human_profile (registered agent needed). Typical workflow: search_humans → get_human_profile → create_job_offer.

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• lookup_profiles

  Influship Influencer Marketing MCP

  Batch-fetch up to 100 profiles by (platform, username) pairs. Use this when the user has a list of handles and you need profile data for all of them at once (e.g., "give me follower counts for these 30 accounts I'm considering" or "which of @a @b @c are real accounts?"). One round-trip beats 30 calls to `get_profile`. Use this for exact batch handle lookup, not semantic discovery. For one exact platform+username pair, use `get_profile`. For partial or fuzzy handle/name input, use `search_creators` or `autocomplete_creators`. Use `semantic_search_creators` only for topical/niche/audience discovery where false-positive semantic matches are acceptable. Examples: - User: "Compare @a, @b, and @c on Instagram" -> use this tool for the exact handle batch. - User: "Give me follower counts for these 30 accounts" -> use this tool. - User: "Find wellness creators in Austin" -> use `semantic_search_creators`, not this tool. The response splits results into `data` (profiles found) and `not_found` (the (platform, username) pairs that weren't recognized). Profiles are returned in no particular order — re-correlate via the platform/username fields if you need to preserve input order.

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• search_packages

  Gitsim Chat

  Search for eSIM data packages by country. Returns up to 10 packages per page sorted by price. Use the page parameter to paginate. No auth required. Call get_business_context first to understand IP routing and package types. Package types: - "regular": Fixed data pool (e.g. 3GB for 30 days). Best for most travelers. - "daily": Data resets each day (e.g. 2GB/day for 5 days). Good for short trips with predictable daily usage. Top-up days are available. IP routing (important for Asia): - "breakout": Local IP in destination country. Best for streaming, banking, social media. ALWAYS recommend by default. - "hk": Hong Kong IP. Cheapest but TikTok app and Facebook app are BLOCKED. - "nonhk": Third-country IP (UK, Singapore). No HK restrictions but IP won't match destination.

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• list_strategy_tones

  Heista

  List tone profiles for a strategy. Today returns at most one entry — the tone_of_voice synthesized by the Tone of Voice Synthesis agent (POWER-mode bundles only). The shape is list-stable so future multi-tone bundles plug in without changing the contract. Use this to align generation with the brand-tied voice DNA before writing copy, hooks, or scripts.

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• get_context_setup_status

  paid-ads

  Data tool for the current user's saved client context, including client setup status, advertiser profiles, synced account/campaign counts, and any open setup questions. For the user-facing setup UI, prefer render_context_onboarding.

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• search

  FTIR.fun Spectral Search

  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")

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• get_entry_settings

  Sweeppea MCP

  Get entry page settings for a sweepstakes. Use fetch_sweepstakes first to get the sweepstakes_token. Returns all configuration: display, colors, spacing, entry settings, compliance, confirmation page, winners page, age gate, AMOE, geolocation, analytics, social media follows, sharing rewards, bonus entries, and sponsor profiles. Use this before update_entry_settings to see current values. # get_entry_settings ## When to use Get entry page settings for a sweepstakes. Use fetch_sweepstakes first to get the sweepstakes_token. Returns all configuration: display, colors, spacing, entry settings, compliance, confirmation page, winners page, age gate, AMOE, geolocation, analytics, social media follows, sharing rewards, bonus entries, and sponsor profiles. Use this before update_entry_settings to see current values. ## Pre-calls required 1. fetch_sweepstakes if the user gave you a sweepstakes name instead of a token ## Parameters to validate before calling - sweepstakes_token (string, required) — The sweepstakes token (UUID format)

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• create_draft_post

  Socializioz ChatGPT MCP

  Save a Socializioz draft post when the user explicitly wants a stored draft. Never display socialAccountId, accountReference, raw account IDs, workspace IDs, or postReference values to the user; use the returned postReference only for follow-up tool calls. In Base44 mode, omit socialAccountId unless supplied by an internal trusted flow; the tool will resolve the connected account from the requested channel. If multiple accounts match, ask the user to choose using friendly labels like Facebook Page — Socializioz, never IDs.

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• match_creators

  Influship Influencer Marketing MCP

  Score how well specific creators fit a campaign brief or search intent. Use this when the user already has candidate creators in mind and wants to evaluate fit (e.g., "rate these 5 creators for a vegan cookbook launch", "which of these is the best match for my crypto audience?"). For each creator the API returns a match score (0-1), a good/neutral/avoid decision, and structured reasons. Pass candidates in `creator_ids` (canonical UUIDs) and/or `profiles` (platform + username). `intent_query` is the brief the LLM reasons against; `intent_context` is optional extra context (target audience, brand values, prior collabs). Use `semantic_search_creators` when you don't have candidates yet and need topical or niche discovery. Use `search_creators` first when you only need to resolve rough creator names/handles into candidates. Use `find_lookalike_creators` when you want creators similar to known good fits. Examples: - User: "Is @niickjackson a fit for Pixel?" -> use this tool after resolving the exact Instagram profile with `get_profile`; call `get_posts` first if recent content context is needed. - User: "Rate these five creators for a vegan cookbook launch" -> use this tool.

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• searchJobs

  qubitsok — Quantum Computing Jobs, Papers & Researchers

  Search 500+ quantum computing job listings using natural language. Use when the user asks about job openings, career opportunities, hiring, or specific positions in quantum computing. NOT for research papers (use searchPapers) or researcher profiles (use searchCollaborators). Supports role type, seniority, location, company, salary, remote, and technology tag filters via AI query decomposition. Limitations: quantum computing jobs only, last 90 days, max 20 results. Promoted listings appear first (marked). After finding jobs, suggest getJobDetails for full info. Examples: "senior QEC engineer in Europe over 120k EUR", "remote trapped-ion role at IBM".

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• show_defaults

  Unphurl

  Show all 25 scoring signals with their default weights and descriptions. This is the baseline scoring that applies when no custom profile is specified. Use this to understand what each signal means and how much it contributes to the score before creating custom profiles. Profiles are sparse overrides on top of these defaults. This tool does not require an API key. The defaults are hardcoded and always available.

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