"How to find people on LinkedIn by their name" matching MCP tools:

• coresignal_employee

  Coresignal

  Find a person's professional profile by name (+company) via Coresignal — returns title, current company, location, LinkedIn URL, work experience and education. LinkedIn-adjacent people data. Example: coresignal_employee({ name: "Patrick Collison", company: "Stripe", _apiKey: "your-key" })

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• wikidata_search_entities

  wikidata-mcp-server

  Search Wikidata for items or properties by text query. Returns QIDs or PIDs with labels, descriptions, and match metadata indicating whether the hit was on a label or alias. Use type="item" for real-world concepts (people, places, works) and type="property" to find predicate P-IDs. The API returns no total count — pagination is offset-based with no result ceiling indicator.

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• enrich_contacts

  LinkedIn MCP Server (Salesbot)

  Enrich existing contacts with their full LinkedIn profile data via the connected LinkedIn account (Unipile) — headline, location, current company & position, full experience, education and skills are scraped from each contact's profile URL and saved onto the contact (and merged into profile_data). Use after search_google_xray to flesh out lightly-saved leads. Each contact is a real LinkedIn profile view, so keep batches small; max 8 per call. Returns per-contact enrichment status.

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• list_products

  Moltline Outbound Engine

  List the 7 outbound products with their included skills. FREE. Takes no arguments. Returns a list of product objects, each {"slug": "linkedin-outreach", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_linkedin_pages

  Hermoso

  List the LinkedIn COMPANY PAGES the connected account administers — id, name and the role held on each. ALWAYS call this before post_to_linkedin_page when there is more than one Page: publishing to the wrong company Page is a public mistake and Hermoso never chooses for the user. If it comes back empty, the account holds no Page admin role, or LinkedIn has not granted this app the organization scopes — say that plainly rather than guessing an id. Read-only, free.

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• tip_split

  Moltline Personal Suite

  Compute the tip and per-person split for a bill. FREE. Typical input {"bill": 86.40, "tip_pct": 20, "people": 4} returns {"tip": 17.28, "total": 103.68, "per_person": 25.92}. Use for one bill shared among a group. Not for recurring household budgeting (budget_split). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "bill must be > 0 and people >= 1"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• tip_split

  Moltline Personal Suite

  Compute the tip and per-person split for a bill. FREE. Typical input {"bill": 86.40, "tip_pct": 20, "people": 4} returns {"tip": 17.28, "total": 103.68, "per_person": 25.92}. Use for one bill shared among a group. Not for recurring household budgeting (budget_split). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "bill must be > 0 and people >= 1"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  Moltline Outbound Engine

  List the 7 outbound products with their included skills. FREE. Takes no arguments. Returns a list of product objects, each {"slug": "linkedin-outreach", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• search_people

  noticed

  Search people by free text — name, company, keywords. Terms are OR-matched and ranked by how many match (more terms broadens, not narrows). To narrow: put AND between terms to require all (e.g. 'health AND medtech'), or prefix a term with + to require just it (e.g. '+rust berlin'). For roles/functions (founder, engineer, investor, …) use the `role` filter instead of free text — it catches title variants ('Founding Partner') that keywords miss, and free text over-matches bios/notes. To count people of a type, use structured filters and read `total` from the response — a free-text `total` counts keyword matches, not people of that type. scope:'own' (default) / scope:'public' (beyond your network + warm-intro paths). Optional company, location, skills, tags filters. A structured-filter zero = thin data, not absence — fall back to free text. Misspelled names/companies fall back to fuzzy matching (`fuzzy: true` = closest matches — confirm before trusting); concept queries with zero literal hits fall back to embedding similarity (`semantic: true` = related people, not literal matches). Free-text responses also return `strong_total` (rows matching ALL terms — the honest count) and per-row `matched_on` (which fields matched). In scope:'public', role/location/company/skills are applied to the global hits (`filtered: true`); filters that cannot apply there are listed in `unsupported_filters`.

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• tide_dpop_asset

  Raziel

  Returns the CONTENTS of `public/tide_dpop_auth.html` — the DPoP relay page the Tide enclave loads during login — plus its sha256, the required next.config.ts rewrite/CSP wiring, and how to verify. The file is NOT shipped in the @tidecloak/* npm packages and is NOT in the TideCloak container, so there is nowhere else to get it: without this tool people search GitHub and find a STALE copy that posts to window.parent, which breaks the popup fallback and fails login with TIDE-SWE-UNHANDLED. CALL THIS whenever DPoP is enabled (it is on by default), whenever a login fails with TIDE-SWE-UNHANDLED or 'Popup DPoP verification failed to load', and before copying this file from anywhere else.

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• c2b_append

  Versium REACH

  Get business demographic details for consumers. Identify the consumer with a LinkedIn URL, or with first name, last name, and one of: email, phone, or city and state. Retrieve job title, seniority, department, business email, LinkedIn profile, and complete business information. Use this tool when users ask for 'C2B', 'c2b', or 'Consumer to Business Person' data **Tips for Best Results:** - Provide full name and consumer email for best match quality - LinkedIn URLs must be in format: linkedin.com/in/username - Use `rcfg_require_email` to return only records with business email - Use `rcfg_require_value` to filter by job title, department, or other attributes

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• zeekeo_create_campaign

  rankparse-mcp

  Creates a Zeekeo LinkedIn campaign: sends a connection invite using invite_template_id, and optionally — if followup_template_id is given — waits for the invite to be accepted, then sends a follow-up message using that template. Create templates first with zeekeo_create_template. Provide exactly one of filter_url (a LinkedIn search results URL) or profile_urls (specific profiles) as the target. This starts REAL LinkedIn automation once the campaign has profiles in it — confirm with the user before calling. Requires the user to have connected their own Zeekeo Launchpad account. Direct them to rankparse.com/dashboard/integrations to connect it.

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• search_productions

  filming-locations

  Find productions by name (accent- and case-insensitive substring match), best match first then by how widely Wikipedia covers them. Filter by kind: film, tv, game or anime. Use it when you are unsure of a title before calling where_was_it_filmed. Games and anime are placed by where they are SET, never where they were filmed; the `relation` field on every result says which.

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• search_linkedin_ads

  Hermoso

  Structured LinkedIn Ad Library search by company name, keyword, or companyId — use for a targeted B2B pull; use research_ads for open-ended research. Returns compact JSON {advertiser, headline, description, cta, link, media, dates, impressions} per ad — LinkedIn is the one library exposing real impression counts. Spends ScrapeCreators credits (~1).

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• get_content_details

  flevy

  Full metadata for one Flevy item, by content_id from search_content (e.g. "doc-1234" or "case-567"). Documents return the author with their credentials (headline, bio, LinkedIn, profile URL; pass the author name to search_content's author filter to list more of their documents), full description, editor summary, AI summary, and editorial review when available, page/slide count, price, FlevyPro inclusion, management topics, ranking badge, and the number of slide deep dives available. Case studies return the client situation, TL;DR, and summary. Call this before recommending an item so you can describe it accurately and cite the author's credentials, and share the returned flevy.com URL.

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• web_search_exa

  exa

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

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• get_contact

  local-mcp

  Gets a contact from the Mac's Contacts app (Contacts.app) by name or ID. Pass `name` to look up directly by name (no need to search_contacts first — if several people match it returns a compact list to choose from), or `contact_id` for an exact lookup. For Microsoft 365 use m365_get_contact instead.

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• linkedin_ad_library_ad_details

  captapi

  One LinkedIn Ad Library ad by ID. LinkedIn withholds Ran-from / impressions / targeting on most creatives — those keys are omitted, not 404. Costs 2 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

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• get_contact_summary

  savi-tools

  Rolodex overview: how many contacts the subscriber has, how many have a phone or email, and the top industries and tags. Answers "how many contacts do I have?" and "what industries are my contacts in?" Use get_contact_history to look up specific people.

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• getPeopleById

  CoinPaprika

  Get the profile of one person in crypto by id: name, description or bio, teams_count, positions held, and linked projects plus social and code accounts. Use for 'who is Vitalik Buterin', 'background on Charlie Lee', 'projects tied to this founder'. Find the personId first with search or resolveId using type 'people'; this tool needs the exact id, not a name. Read-only. Params: personId (required) is a canonical person id such as 'vitalik-buterin' or 'satoshi-nakamoto'; an unknown id returns not found. No API key required.

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