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

• linkedin_render_account_health

  paid-ads

  Preferred user-facing LinkedIn account analysis and account health dashboard. Renders the LinkedIn account readiness report with setup recommendations, probe evidence, and technical details. Use this directly when a user asks for LinkedIn account analysis, account health, connector readiness, setup diagnostics, or whether a LinkedIn Ads account is ready for reporting. It can take healthPayload from linkedin_get_account_health or run the same health checks directly. If accountId is omitted, the most recent LinkedIn account from session memory is used when available.

  Connector

• linkedin_render_creative_comparison

  paid-ads

  User-facing LinkedIn creative comparison visual report renderer. Current app template: ui://linkedin/creative-comparison-v4.html. Use this directly when a user asks for a LinkedIn creative comparison visual report, creative performance report, creative winners/losers, or which creative concepts are performing strongest. It renders the visual MCP app with Overall/campaign views, creative action cards, primary results, diagnoses, and bottleneck diagnosis. It can either take comparisonPayload from linkedin_compare_creative_performance or fetch the comparison directly. For account-wide creative analysis, pass accountId and omit campaignId/campaignIds, or pass advertiserName/query so saved advertiser context or live account-name matching can resolve the LinkedIn account. Name-only account-wide requests are supported; do not claim the renderer requires a numeric accountId until this tool returns an account-selection blocker. lookbackDays accepts numbers and string aliases such as "30d", "30 days", and "past 30 days"; do not claim a numeric lookback is required. If accountId and name/query are omitted, the most recent LinkedIn account from session memory is used when available. For campaign-specific creative analysis, pass campaignId or campaignIds; if accountId is also supplied as parent context, set scope to campaign when possible. accountId plus campaignIds is accepted as a campaign-set compatibility shape.

  Connector

• 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.

  Connector

• ensembl_list_species

  ensembl-mcp-server

  List species supported by Ensembl with display name, common name, assembly, taxon ID, and division. Required discovery step — species names like homo_sapiens are opaque to non-biologists and are the input format every other Ensembl tool expects. Filter by division to select one; use nameContains to find a species by partial name match. With no division, returns the endpoint default division — the vertebrates (~356 species on the default GRCh38 endpoint); pass a division to list that division.

  Connector

• gtm_leads

  Vaaya

  Manage the user's campaign-free lead repository (people to reach out to — prospects, candidates, targets, investors; differently tagged for different uses). action='add' upserts people you already have (paste a list); each person = { first_name, last_name, title, company, email, linkedin_url, why_prioritized?, hook?, source? }; deduped per person within the user's scope so re-adding updates, never duplicates. action='list' returns leads (optional `q` search, `tag_id`/`segment_id` membership filter, `limit`). action='get' returns one lead by `id`, with its tags and any inbound reply conversations linked to them. action='tag' applies labels: { id | ids:[…], tags:["founder","warm-intro"] } (bulk-capable; creates missing tags, idempotent). action='untag' removes a label: { id | ids:[…], tag_id }. To DISCOVER new people via paid search, use `gtm_leads_find`; to group leads, use `gtm_segments`.

  Connector

• get_data_source_categories

  Demand Discovery AI

  Returns the four behavioral data-source buckets - Search & attention, Conversation & pain, Adoption & spend, Capital & hiring - with each bucket's tagline and what it captures. Use when a user asks "what data sources do you use?", "where does the Demand Score come from?", or wants to understand how Demand Discovery AI differs from passive validation tools (which only triangulate the first two buckets). This four-bucket framing is the core competitive moat. The specific connector list is intentionally not public. Trigger phrases: "what data sources", "where does the demand score come from", "behavioral data sources", "the four buckets", "search and attention bucket", "conversation and pain bucket", "adoption and spend bucket", "capital and hiring bucket", "how many data sources", "what kind of data sources", "where do you find the evidence", "how do you find people complaining", "how do you find prospects", "what signals do you look for", "where does the behavioral evidence come from".

  Connector

• cyanheads_search

  cyanheads-mcp-server

  Search fleet tools and servers by natural-language description. Returns ranked matches with brief summaries and the server each tool belongs to. Use scope "servers" to find which server handles a workflow; use the default scope "tools" to find specific tools. Call cyanheads_describe on a result name to get install snippets and the connection URL.

  Connector

• close_list_contacts

  Close Crm

  List contacts (people) in Close. Returns a `data` array of contacts with id, lead_id, name, title, emails, and phones, plus `has_more` / `total_results`. Optionally filter to one lead with `lead_id`. Page with `_limit` / `_skip`.

  Connector

• read_record

  Emer Ai Tools

  Read one Emercoin NVS (Name-Value Storage) record by its full name — an agent's identity (`ai:gh:<github_id>`) or a memory (`ai:gh:<github_id>:mem:<hash>`) written by `register_identity` / `store_memory`. Returns the confirmed on-chain record, or a `pending` one still in the mempool — the `status` field ('confirmed' | 'pending') distinguishes them. Read-only, no sign-in required; use `whoami` to find your own github_id. Returns null fields for a name that does not exist.

  Connector

• how_to_give_feedback

  life. scored.

  How to suggest a better weight, a fresh source, or a new rule via GitHub, so improvements from many people aggregate in the open.

  Connector

• search_google_xray

  LinkedIn MCP Server (Salesbot)

  Google X-Ray search for public LinkedIn profiles via Google operators (site:linkedin.com/in). Useful when you don't want to consume LinkedIn search limits. Found profiles are saved into your contacts (in a 'Google X-Ray' list, deduplicated by profile URL) and the tool returns their contact_id values. To move them into the CRM, add them to a campaign with add_contacts_to_campaign (auto-creates CRM leads) or use a CRM tool like set_deal_stage. Paginates Google results and auto-filters duplicates.

  Connector

• zambo_pulse

  Zambo AI Tools

  Get live zambo.dev platform stats — tool calls today, active pass holders, sparks fired, proofs certified, day passes active, days live. Returns real-time social proof numbers. Call when a user asks 'is this popular?', 'how many people use this?', 'is it active?', or wants to know platform health. Free, always available, no auth required.

  Connector

• search

  tela

  Keyword (full-text) lookup over title + body, ranked + snippet-highlighted. Use to find a page you can name or that contains an exact term/identifier/error string. Works WITHOUT an embedder (always available). Optional space_id narrows to one space. To answer a question or gather material on a topic by meaning, use `research` instead.

  Connector

• 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.

  Connector

• messages_send

  dialogbrain

  Send a message to a thread, channel, or contact. Supports Telegram, Email, LinkedIn, and other connected channels. For LinkedIn posts (comment_thread kind), this posts a comment on the post. Can automatically resolve recipients and channels when not specified. Can send files/images/documents as attachments — pass `attachments=[file_id, ...]` with integer file IDs obtained from collections.list_files, search.files, or files.search. `text` is optional when attachments are provided.

  Connector

• get_data_source_categories

  Demand Discovery AI

  Returns the four behavioral data-source buckets - Search & attention, Conversation & pain, Adoption & spend, Capital & hiring - with each bucket's tagline and what it captures. Use when a user asks "what data sources do you use?", "where does the Demand Score come from?", or wants to understand how Demand Discovery AI differs from passive validation tools (which only triangulate the first two buckets). This four-bucket framing is the core competitive moat. The specific connector list is intentionally not public. Trigger phrases: "what data sources", "where does the demand score come from", "behavioral data sources", "the four buckets", "search and attention bucket", "conversation and pain bucket", "adoption and spend bucket", "capital and hiring bucket", "how many data sources", "what kind of data sources", "where do you find the evidence", "how do you find people complaining", "how do you find prospects", "what signals do you look for", "where does the behavioral evidence come from".

  Connector

• 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.

  Connector

• read_record

  Emercoin Agent

  Read one Emercoin NVS (Name-Value Storage) record by its full name — an agent's identity (`ai:gh:<github_id>`) or a memory (`ai:gh:<github_id>:mem:<hash>`) written by `register_identity` / `store_memory`. Returns the confirmed on-chain record, or a `pending` one still in the mempool — the `status` field ('confirmed' | 'pending') distinguishes them. Read-only, no sign-in required; use `whoami` to find your own github_id. Returns null fields for a name that does not exist.

  Connector

• trip_discovery

  DC Member API

  GET /trips/:tripID/discovery — Get the discovery block for a trip Discovery-only read for a trip. Returns the same `discovery` block as `GET /trips/:tripID` (people, fullPool, whyToMeet, events, overlappingTrips) without the trip body. Useful for callers that just want "who should I meet on this trip?" — the AI agent gets the ranked top-10 + their `whyToMeet` paragraphs in a single request. Use `?include=` to subset the response — comma-separated from `people,fullPool,whyToMeet,events,overlappingTrips`. Default is all. Common patterns: - `?include=people,whyToMeet` — top-10 picks + their AI-written "why you should meet them" paragraphs (keyed by userID, each carrying `{ text, generatedAt }`) - `?include=fullPool` — every visible DCer travelling/local during the trip window - `?include=events` — just events in the destination city during the trip window Open to any authenticated DCer; hidden + guest profiles are filtered out.

  Connector

• 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" })

  Connector