"A way to find people on LinkedIn using their names" 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.

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• resolve_url

  Veezee: LinkedIn people & company data for agents

  Identify what a LinkedIn URL points at before fetching it. Give any LinkedIn profile, company, or post URL (utm params, www/m subdomains, trailing slashes are fine); get back {type: person|company|post, id, handle, canonical_url}. For profile URLs, id is the stable person URN; for company URLs, id is the stable company URN; for post URLs, id is the activity URN extracted from the URL. For people, use the returned handle or id with get_profile or get_posts. For companies, use the returned HANDLE with get_company or get_posts; the company URN/id is a search_people filter input, not a fetch identifier. Costs 2 credits. Skip this tool when you already have a slug, URN, or clean URL: get_profile and get_company accept those directly, so resolving first would waste 2 credits. Not for non-LinkedIn URLs; it returns INVALID_INPUT for those.

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• linkedin_resolve_url

  linkedin

  Identify what a LinkedIn URL points at before fetching it. Give any LinkedIn profile, company, or post URL (utm params, www/m subdomains, trailing slashes are fine); get back {type: person|company|post, id, handle, canonical_url}. For profile URLs, id is the stable person URN; for company URLs, id is the stable company URN; for post URLs, id is the activity URN extracted from the URL. For people, use the returned handle or id with linkedin_get_profile or linkedin_get_posts. For companies, use the returned HANDLE with linkedin_get_company or linkedin_get_posts; the company URN/id is a linkedin_search_people filter input, not a fetch identifier. Costs 2 credits. Skip this tool when you already have a slug, URN, or clean URL: linkedin_get_profile and linkedin_get_company accept those directly, so resolving first would waste 2 credits. Not for non-LinkedIn URLs; it returns INVALID_INPUT for those.

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• bulk_transfer_ens_names

  Name Whisper — ENS Intelligence Layer

  Transfer multiple ENS names in a single transaction via Multicall3 — bulk send. Much cheaper and faster than transferring names one at a time. Supports up to 20 names per batch. Automatically detects whether each name is wrapped (NameWrapper/ERC-1155) or unwrapped (BaseRegistrar/ERC-721) and builds the correct transfer call for each. All names can go to the same recipient or to different recipients — specify a toAddress per name. Each toAddress may be a 0x address OR an ENS name (resolved to its address record automatically); pass what the user gave you and never use get_name_details to resolve a recipient. Conversational flow for "send all my names" / "transfer my names": first call get_wallet_portfolio to find the names, present the FULL list that will be transferred, confirm the recipient, and get explicit confirmation (this is IRREVERSIBLE). Only THEN call this tool. NEVER auto-transfer without explicit confirmation. Requirements: - The fromAddress must currently own ALL names in the batch - All addresses must be valid Ethereum addresses - Names must be registered (not expired) WARNING: This transfers FULL ownership of every name. Recipients gain complete control. Resolver records (avatar, addresses, etc.) are NOT affected by transfer — they stay on each name. After transfer, consider using bulk_set_records to update ETH address records on the transferred names.

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• enumerate_entities

  Name Whisper — ENS Intelligence Layer

  Enumerate ENS-friendly labels for a finite real-world entity category and report which are available vs registered. USE THIS for ANY finite set of real-world people, companies, teams, or works — including queries that name a ROLE or PROFESSION rather than a league, e.g. "which tech founders have an available .eth?", "available CEOs / politicians / authors / footballers", "famous musicians I can register", "NBA hall of famers", "available Pixar films", "F1 drivers", "Beatles songs that are open". If the user is asking to find/register the names of actual real-world entities (not a vibe or an ENS club), this is the tool — even when the category sounds soft ("tech founders", "crypto founders", "famous CEOs") it is still a finite real-world list, so come straight here; do NOT fall back to search_ens_names for it. The tool generates verified, correctly-spelled ENS labels — do NOT enumerate entity names from your own context and pass them to check_availability, because models routinely misspell long-tail names (scottiepippin instead of scottiepippen) or invent people who don't exist (e.g. "johncarlton" as an NBA HOFer). This tool exists precisely to avoid that. DO NOT use this for: - Vibes / themes ("luxury watch names", "edgy crypto names") — use search_ens_names with concept_search instead. - ENS-native categories ("10k club", "3-letter words") — use search_ens_names with collection_search. - Single-name lookups — use check_availability. Returns a list of entries grouped by status. Each entry has the proper name (e.g. "Scottie Pippen") alongside the ENS label (scottiepippen.eth), so you can show users the human-readable name in your reply.

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• autocomplete_creators

  Influship Influencer Marketing MCP

  Autocomplete creator names, usernames, or display names from partial input. Use this for fast lookup when the user types a partial handle or name and you need to resolve it to canonical creator IDs (e.g., "find @cris" or "who's that fitness coach called Jane?"). Cheap and fast — prefer over `search_creators` for handle-style queries where the user already knows roughly who they want. Use `get_profile` instead when the user gives an exact platform+username pair. Use `search_creators` for the same fuzzy creator lookup behavior with a less typeahead- specific name. Use `semantic_search_creators` only for discovery by topic, niche, audience, geography, or content style, not for resolving a known creator. Examples: - User: "Who is that fitness coach called Jane?" -> use this tool. - User: "Find @cris..." -> use this tool to resolve the partial handle. - User: "Pull @niickjackson on Instagram" -> use `get_profile`, not this tool. Returns a short list of matching creators with their IDs, platforms, and display names. Use the IDs returned here as input to `get_creator`, `find_lookalike_creators`, or `match_creators` for downstream operations.

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• start_agentic_launch

  Demand Discovery AI

  Kick off Day 1 of the 90-day Agentic Launch for a completed Demand Discovery Report. Demand Discovery surfaces named prospects matching the idea's ICP and DRAFTS the first outreach batch. It sends NOTHING automatically - the user reviews and sends from their hosted manage page. Outreach is drafted to come from Amy @ Demand Discovery, with replies routed to the user's own email. Call this after a paid report is "ready" and the user wants to act on it (e.g. "generate prospects", "start agentic launch", "find me people to talk to", "yes, do the outreach"). Pass the reportId, the user's email, and the alTriggerToken from the ready report if you have it. The email MUST be the address the user themselves provided earlier in this conversation (their report-delivery email) - if you don't have it in context, ask the user first; NEVER invent one or use a placeholder like user@example.com (placeholders are rejected and the launch will not start). The response returns a manageUrl where the user reviews/sends the drafted outreach (and can switch the sender to their own Gmail).

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• search_people

  Veezee: LinkedIn people & company data for agents

  Find people on LinkedIn by keywords and filters. The right tool when you have a name, role, or 'who is the X at Y' question without a profile URL. Pass keywords (free text: name, title, or both) and any of first_name, last_name, title, school, current_company, past_company. If keywords is omitted it is derived from the name or title filters; school or company filters alone are rejected with INVALID_INPUT, so include keywords with those. Company filters accept a company name, slug, numeric id, or URN; names are resolved for you. Costs 10 credits including the first 10 results; each further 10 results add 1 credit (limit max 30; keyless and trial callers max 10). A cursor page is a NEW call priced the same way by its own limit, so one limit=30 call is much cheaper than three limit=10 pages; prefer a larger limit over paginating. Do NOT combine a company NAME filter with limit=30: name resolution spends one of the call's three internal fetches, so that combination is rejected. With a company name keep limit<=20; for limit=30 pass the company's numeric id or URN (get_company returns both). Returns name, position, location, urn, public_identifier per result, a cursor for the next page, and total_matches. Results with is_anonymous=true are private profiles; do not pass them to get_profile. For one known person with a URL/slug, call get_profile directly instead.

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• reddit_search

  reddit

  Search all of Reddit by keywords. type picks the target: posts (default), comments (what people actually say about a product, problem, or brand -- unique to Reddit search), subreddits (find communities), users. Pass query as free text up to 256 characters; decompose broad topics into several narrower queries, since result depth per query is capped upstream around a few hundred results. sort applies to posts (relevance|top|new|hot|comment_count) and comments (relevance|top|new); range (past_hour..all_time) applies to posts only; both are rejected with INVALID_INPUT elsewhere. Costs 6 credits per page; a cursor page is a NEW call priced the same way. Returns one page of summaries (author, title or comment text, upvotes, comment_count, created_at, permalink, id) with a cursor; there is no server-side time window on comment search, so for monitoring filter on created_at yourself and poll with sort=new. Fetch full post bodies and discussion threads with reddit_get_post; read one community's feed with reddit_get_subreddit_posts. For high-volume recency sweeps across X instead, use x_search.

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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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• start_agentic_launch

  Demand Discovery AI

  Kick off Day 1 of the 90-day Agentic Launch for a completed Demand Discovery Report. Demand Discovery surfaces named prospects matching the idea's ICP and DRAFTS the first outreach batch. It sends NOTHING automatically - the user reviews and sends from their hosted manage page. Outreach is drafted to come from Amy @ Demand Discovery, with replies routed to the user's own email. Call this after a paid report is "ready" and the user wants to act on it (e.g. "generate prospects", "start agentic launch", "find me people to talk to", "yes, do the outreach"). Pass the reportId, the user's email, and the alTriggerToken from the ready report if you have it. The email MUST be the address the user themselves provided earlier in this conversation (their report-delivery email) - if you don't have it in context, ask the user first; NEVER invent one or use a placeholder like user@example.com (placeholders are rejected and the launch will not start). The response returns a manageUrl where the user reviews/sends the drafted outreach (and can switch the sender to their own Gmail).

  Connector

• linkedin_search_people

  linkedin

  Find people on LinkedIn by keywords and filters. The right tool when you have a name, role, or 'who is the X at Y' question without a profile URL. Pass keywords (free text: name, title, or both) and any of first_name, last_name, title, school, current_company, past_company. If keywords is omitted it is derived from the name or title filters; school or company filters alone are rejected with INVALID_INPUT, so include keywords with those. Company filters accept a company name, slug, numeric id, or URN; names are resolved for you. Costs 10 credits including the first 10 results; each further 10 results add 1 credit (limit max 30; trial keys max 10). A cursor page is a NEW call priced the same way by its own limit, so one limit=30 call is much cheaper than three limit=10 pages; prefer a larger limit over paginating. Do NOT combine a company NAME filter with limit=30: name resolution spends one of the call's three internal fetches, so that combination is rejected. With a company name keep limit<=20; for limit=30 pass the company's numeric id or URN (linkedin_get_company returns both). Returns name, position, location, urn, public_identifier per result, a cursor for the next page, and total_matches. Results with is_anonymous=true are private profiles; do not pass them to linkedin_get_profile. For one known person with a URL/slug, call linkedin_get_profile directly instead.

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• contact_broker

  Venturu

  Send a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.

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• contact_broker

  mcp-server

  Send a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.

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• fill_form

  form fill-mcp

  Fill a PDF form with the given field values and save the result to disk. WORKFLOW: 1) Call list_form_fields first to get exact field names and their x/y positions. 2) Use position coordinates to confirm which field is which — higher y = higher on page. 3) Pass exact field names from list_form_fields here. Never guess field names. Use for single-page or short forms (under 5 pages). Use fill_form_multipage for longer forms. Returns ok:false with unknown_fields if ALL provided field names are invalid. Returns ok:true with a warnings.unknown_fields list if SOME names are invalid (partial fill).

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• lyra_get_shared_availability

  lyra-mcp-server

  Returns busy windows for YOU plus a set of named attendees from your Lyra contacts, within a time window. For each attendee you provide, the tool looks up whether their Lyra profile has a connected Google calendar; if so, their busy blocks contribute to the aggregated suggested_free_intervals. If not (or if they're not a linked Lyra profile), they're marked requires_manual_confirm: true so you know to ask them directly. Cap of 8 attendees per call. Privacy: per-attendee busy time ranges are returned, never event titles or summaries. Use this when you need to find a time that works for several people at once. Requires an active Google calendar connection on your own Lyra account and API key authentication.

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• autocomplete_creators

  Influship

  Autocomplete creator names, usernames, or display names from partial input. Use this for fast lookup when the user types a partial handle or name and you need to resolve it to canonical creator IDs (e.g., "find @cris" or "who's that fitness coach called Jane?"). Cheap and fast — prefer over `search_creators` for handle-style queries where the user already knows roughly who they want. Use `get_profile` instead when the user gives an exact platform+username pair. Use `search_creators` for the same fuzzy creator lookup behavior with a less typeahead- specific name. Use `semantic_search_creators` only for discovery by topic, niche, audience, geography, or content style, not for resolving a known creator. Examples: - User: "Who is that fitness coach called Jane?" -> use this tool. - User: "Find @cris..." -> use this tool to resolve the partial handle. - User: "Pull @niickjackson on Instagram" -> use `get_profile`, not this tool. Returns a short list of matching creators with their IDs, platforms, and display names. Use the IDs returned here as input to `get_creator`, `find_lookalike_creators`, or `match_creators` for downstream operations.

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• ask_wiremi

  Wiremi Marketing MCP

  Ask Wiremi anything about ROSCAs, savings circles, the Wiremi Passport, or how Wiremi works, in the user's own words. Routes the question to the best Wiremi answer and always points to where to go next. Use this when the other tools do not exactly match what the user asked. The question text is logged (no other personal data) so Wiremi can see what real people ask and improve its answers, the way Search Console shows real search queries.

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• publish_linkedin_post

  LinkedIn MCP Server (Salesbot)

  Create a LinkedIn post on behalf of a connected profile. By default the post is saved as a 'draft' in the LinkedIn Posts page so the user can review/edit it before publishing. Set auto_publish=true to publish immediately — that path still respects the user's MCP human-in-the-loop setting (when approval is required, the post stays as a draft and the user must publish it from the LinkedIn Posts page in the app). A random 30–180 s anti-detection delay is applied before the publish call. Attachments are not supported via MCP — add images in the in-app post editor.

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• goal-resolve-escalation

  Planner (proof-of-done)

  Resolve a pending AC escalation. Owner decides: edit (provide new AC text), split (move AC to a child goal), or reject (agent must find another way). All prior evidence on the AC is deleted for edit/split so the agent must submit fresh proof.

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