"A tool for finding people on LinkedIn by their name" matching MCP tools:

• list_productsA

  Moltline Outbound EngineA

  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.

  ConnectorNo auth

• list_productsA

  Moltline Outbound EngineA

  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.

  ConnectorNo auth

• search_linkedin_peopleA

  SliqA

  <summary>Search LinkedIn for people — by name, by a specific person's connections, or by profile filters — and return the matching profiles. Provide `keywords` (a name or search term) or a scope filter (`connections_of` / `advanced_keywords`). One call runs one query, returning ~10 matches by default (one page). To go deeper on a single query — "find people in my network matching my ICP" — pass `max_results` (up to 100): the tool pages through the matches for you, each ~10-profile page counting as one search against the daily budget. To search *different* people — a list of names, or one filter per company — loop this tool inside a `run_code` block, one call per name or company (that's breadth; `max_results` is depth on one query). Searches are paced a few seconds apart and serialized across this user's LinkedIn work, so a deep search or a long loop can take a couple of minutes; tell the user to expect a short wait before a large run. If a search comes back paused or rate-limited, stop and tell the user which searches remain — the account is paused and further calls won't run until it lifts. Scope filters combine with `keywords` and can be used alone for a single filtered search: - `connections_of` — restrict to the first-degree connections of specific people, passed as their `provider_id`s (as returned by an earlier search or profile lookup). To work up to a buyer through someone the user just connected with, pass that person in `connections_of` and the target company in `advanced_keywords={'company': 'Acme Corp'}` to surface who they know there. `network_distance` is a separate filter on the user's *own* degree and combines with this — add [2] to keep just the connections the user isn't already directly linked to. - `advanced_keywords` — native LinkedIn keyword sub-filters: a dict with any of `first_name`, `last_name`, `title`, `company`, `school` (each a string). - `profile_language` — ISO 639-1 codes (e.g. ['en']) that narrow any of the above to profiles written in those languages. A refinement, not a search on its own — pair it with keywords or another filter. When this runs in an agent, the matches are saved and linked to the workspace Output tab automatically (deduped by profile). Pass `list_name` (a short slug) to name their list — a discovery search, the people connected to someone, prospects to work through; reuse the same slug across a loop or follow-up searches to gather everything into one list. Absent a slug, matches land in the 'default' list. Outside an agent, results are returned only. Returns up to `max_results` matching profiles with provider_id, name, headline, network_distance, location, and profile_url — each match's `headline` shows their current role and company (e.g. to see which companies 2nd-degree matches work at). `total_count` is LinkedIn's full match count for the query when it returns one, but LinkedIn now omits it on most Classic searches (so it's often null): only say "showing N of ~M" when it's a number exceeding the profiles returned, and never invent a total. Use `has_more` — True when more results exist beyond those returned — to decide whether to offer to pull more. Present the results to the user so they can pick the right person. An `error` about being "heavily queued" is transient pacing back-pressure — retry shortly rather than reporting it as not found. That field list is the whole of it — a search result carries no connection count, follower count, or employment history. Present what comes back as it is; a search the user wanted to look at is finished at that point. When the ask genuinely needs one of the missing fields — a connection-count threshold, employment history to personalize from — pass the matches' profile URLs to `enrich_linkedin_profiles`, which returns them for the whole list in one paid call (`connections_count` is the field a connection-count filter reads) and spends no LinkedIn account budget. When the decision also turns on whether the user is already connected to them, use `setup_linkedin_sequence(action_type='resolve')` instead; connection status is the one thing enrichment cannot answer. Rate-limited — shares one daily LinkedIn search budget with all other LinkedIn people searches.</summary> <returns> <description>On success, a dict `{'success': True, 'profiles': [...], 'total_count': int | None, 'has_more': bool, 'searches_remaining_today': int}`. `profiles` holds up to `max_results` matches; `total_count` is the query's full match count when LinkedIn returns one (often null since its Aug-2026 Classic Search change), so lean on `has_more` for whether more results exist; and `searches_remaining_today` is the post-search budget, so you can size a follow-up loop without re-checking. In an agent, also `saved_to_list` (the list the matches were saved to) and `saved_count`; outside an agent, a passed `list_name` yields a null `saved_to_list` with a `persist_note`. If the account tripped its pause partway through paging, the (still valid) partial results come back with `paused: True` and a `note` — surface it: further searches won't run until the pause lifts. On a failed search: `{'success': False, 'profiles': [], 'error': ..., 'searches_remaining_today': int}`. On a pre-flight refusal (daily limit reached or account paused), `searches_remaining_today` is omitted: `{'success': False, 'error': ...}`.</description> </returns>

  ConnectorOAuth

• search_target_group_criteriaA

  Metadata MCP ConnectorA

  Get available criteria and their supported values (names and IDs) for target group creation/updates. USE FOR: "what targeting criteria are available?", "what options for [criteria type]?", "supported values for industries/seniority/job functions", "how to search job titles/interests/member groups?", validate criteria before creating target group, get valid IDs for create_target_group. CRITERIA TYPES: 1. LIST-BASED (returns predefined options): - age-ranges: Age range options - company-categories: Company classifications - company-growth-rates: Growth rate ranges - revenues: Revenue ranges - employees: Employee count ranges - industry-taxonomy: Industry codes/names - jobFunctions: Job function categories - seniority: Seniority levels - followed-companies: Company follow options - locations: Geographic data (MANDATORY as FIRST criteria for LinkedIn) - use search_terms for filtering 2. SEARCH-BASED (use search_terms): - job-title: Search job titles (reference_type: LINKEDIN_JOB_TITLES) - member-groups: Search LinkedIn groups (reference_type: LINKEDIN_MEMBER_GROUPS) - member-skills: Search professional skills - interests: Search interests (reference_type: LINKEDIN_INTERESTS) - traits: Search behaviors (reference_type: LINKEDIN_TRAITS) 3. NUMERIC: years-of-experience (0-12, not retrieved via this tool) OPERATION MODES: - List: search_target_group_criteria(channel="LINKEDIN", criteria_type="seniority") - Search: search_target_group_criteria(channel="LINKEDIN", criteria_type="job-title", search_terms=["engineer"], exact_match=false) - Direct: search_target_group_criteria(channel="LINKEDIN", reference_type="LINKEDIN_JOB_TITLES", search_terms=["engineer"]) RESPONSE: Array of {externalId, name}. Use externalId in target group config, show name to users. CHANNEL: Only LINKEDIN supported.

  ConnectorAPI key

• call_toolA

  Opus Growth, Ad Platforms MCP ConnectorA

  Run a READ-ONLY Opus tool by name — the gateway to every reporting/listing capability that is not in your visible core set. Use search_tools(query) FIRST to get the exact name and its argument schema, then call it here. name = exact tool name; arguments = that tool's parameters as an object. Reads data from the advertising and analytics APIs the user has connected (Google Ads, Microsoft Advertising, Meta, TikTok, LinkedIn, Search Console, GA4, YouTube, Tag Manager, Google Business Profile) plus Opus Growth's own SEO/hosting data. This gateway NEVER writes: if the tool you name modifies data it is refused and you are told to use call_write_tool. Arguments are validated against the tool's schema server-side; on a mismatch you get a precise error telling you what to fix. Credits and access rules behave exactly as calling the tool directly.

  ConnectorOAuth

• linkedin_search_peopleA

  Veezee: LinkedIn people & company data for agentsA

  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. current_company names are matched by LinkedIn's own company search: typo-tolerant and fuzzy, so results can include people whose headline merely mentions the company; when you need exact filtering, pass the numeric id or URN (linkedin_get_company returns both). past_company names are resolved to an id 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 past_company NAME or a company-URL filter with limit=30: resolving those spends one of the call's three internal fetches, so that combination is rejected; keep limit<=20 with them or pass the numeric id. current_company names never spend a fetch, so they combine with any limit. 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.

  ConnectorOAuth

• search_linkedin_peopleA

  LinkedIn MCP Server (Salesbot)A

  Search LinkedIn people. RECOMMENDED FOR PROSPECTING: set decisionMakers:true, provide company, departments and limit 20-30. Salesbot resolves the company, performs ONE company-scoped provider search (Sales Navigator also applies seniority), then ranks the returned senior employees locally by department. This is broader and safer than retrying exact titles. Use title/titles only when an exact role is required. EXISTING CONNECTIONS reads only the local cache and consumes zero search quota. The workspace setting selects Standard/Classic or Sales Navigator automatically. Respect retry_after; never immediately retry a protected or timed-out request. On LINKEDIN_PROVIDER_TIMEOUT use search_google_xray, then retry LinkedIn only after the stated delay.

  ConnectorNo auth

• list_automationsA

  mcpA

  List multi-step email sequences and how many people are currently in each, with the id each one is enrolled by. Newest first, at most 100 per call; while has_more is true, next_cursor passed back as cursor returns the next page. A 'paused' automation holds its people on their current step rather than ending their sequence: they stay 'active' and continue from that step once it is active again. list_automation_enrollments lists who is on one, and who left and why.

  ConnectorNo auth

• campaignstack_extract_company_employeesA

  campaignstackA

  Read a company's LinkedIn People page on one of the workspace's connected accounts (up to 1000 profiles, LinkedIn's own display ceiling; optionally filtered by job titles). Call this when the user asks who works at a company, or wants a company's people turned into leads. Employees land as shared leads tied to the company - re-running updates them, never duplicates. They are NOT added to any lead list; read them with campaignstack_list_company_employees and act with campaignstack_add_leads_to_list. The job runs in the background; one extraction per company at a time. Use campaignstack_list_companies to find company IDs.

  ConnectorAPI key

• people_searchA

  PeopleSearch.imA

  Search a global professional database in plain English (for example 'Heads of Marketing at Series B SaaS in New York') and get a sample of matching people plus the true total match count. Results are masked previews (a masked name, role, industry, company size and location) and each one carries an opaque `token`. Searching is FREE and spends no credits: use it to validate that the right people exist before you pay. If nothing matches exactly, the least essential filters are dropped automatically and `broadenedBy` names them. To get a person's real name, LinkedIn and verified email, pass their token to reveal_profile, or use find_people to unlock a batch in one call.

  ConnectorNo auth

• find_peopleA

  PeopleSearch.imA

  The list-building tool. Re-runs a plain-English people search exactly as people_search does (including its automatic broadening, reported in `broadenedBy`) and unlocks up to `count` full profiles in ONE atomic charge: 1 credit per newly unlocked person, and anyone you already own is free. Returns each person's real name, title, company, location, LinkedIn URL and an `id`. Emails are NOT fetched here (that is a separate credit): after unlocking, call fetch_email with each person's `id` to get their verified work email. WARNING for autonomous use: this can spend up to `count` credits in a single call, so choose `count` deliberately and confirm with the user before large batches. Returns an out-of-credits error instead of overspending.

  ConnectorNo auth

• particle_catalogA

  particle-proA

  Browse the full Particle tool catalog. Your tools/list shows only the default categories, but EVERY public Particle tool is callable by name regardless of what was advertised — call this tool to discover the rest. Without arguments: the categorical menu (every category with tool names, one-line summaries, and an `↳` line listing each tool's expand options). With `category`: the full input schema for each of that category's tools, ready to call. Two conventions the one-line summaries don't convey, so read tools through this lens: - Tools are lean by default and EXPAND. Most return a minimal payload and opt into richer sections via an `include` array (e.g. a company's people, products, and competitors; a person's roles and podcast appearances) or change behavior via a `mode`/`format` switch. The `↳` line names these — a tool does far more than its summary alone implies. - Responses are a graph; slugs are edges. A slug a tool returns (person, company, podcast, episode, publisher, guest) is a valid input to the other tools, so you resolve once and then traverse: company → its people → a person's podcast appearances → that episode's transcript and every entity in it. Categories on offer: - `system` (always-on): Discovery meta-tools: browse the full tool catalog and call any tool by name. - `podcasts` (default): Resolve podcasts, list and fetch episodes, search transcripts, and find entity mentions. - `people` (default): Resolve people and entities to canonical handles and fetch person profiles. - `companies` (default): Resolve companies and fetch company profiles with people, products, and competitors. - `topics` (default): Browse the hierarchical topic taxonomy used to classify podcast episodes. - `podcast_rankings` (default): Podcast chart rankings: current charts, movers, and ranking history. - `podcast_guests` (default): Podcast guest directory, trending guests, and per-guest appearance profiles. - `podcast_advertising` (opt-in): Podcast advertising intelligence: sponsor rosters, ad presence, and sponsor leaderboards. - `podcast_publishers` (opt-in): Podcast publisher profiles with their shows, bias profile, and suitability profile. - `podcast_ratings` (opt-in): Listener review ratings for podcasts: summaries and recent rating lists. - `podcast_bias` (opt-in): Corpus-wide political-bias views: publisher leaderboards and publishers by bias result. - `podcast_suitability` (opt-in): Corpus-wide GARM brand-suitability views: publisher leaderboards and category exposure. - `alerts` (default): Create and manage alerts that watch entities for podcast mentions or speaker appearances, preview match frequency, and review the matches an alert has caught. - `radar` (opt-in): Display selected research results as embedded Radar cards, with a Markdown fallback. Rendering is free and does not fetch data. Opt-in categories can also be advertised on tools/list by adding `?include=<category>` (comma-separated, or `all`) to the connection URL, or the X-Particle-Include header. `?exclude=` hides default categories; `?tools=<name,...>` pins the advertised list to exact tools instead. Discovery is free; tool execution is metered and plan-gated as usual.

  ConnectorOAuth

• find_phone_numberA

  SliqA

  <summary>Find phone numbers for one or more people from their LinkedIn URLs, via Airscale. Pass a list of LinkedIn profile URLs — one entry for a single person, all of them at once for a batch (they are looked up in parallel, costing one tool call against the loop guard, not N). Returns one result per URL in the same order. Airscale brokers providers like RocketReach. Persists nothing — use the returned numbers however the agent needs them (e.g. tell the user, or stash them on prospects via `update_prospect`). A LinkedIn profile URL is the only accepted input — this tool cannot look a person up by email or name. When a record (a HubSpot/CRM contact, a prospect row, a spreadsheet line) has no LinkedIn URL but does have the person's email, first call `find_linkedin_url(email=...)` to resolve one, then pass that URL here. Apply this resolve-then-lookup step to every record, not just the first; skip the phone lookup for any person you cannot get a URL for. Costs 8 Sliq credits per number found, when run on Sliq's shared Airscale account. Misses (no number on file) and upstream failures are free. A worst-case check runs up front on the Sliq path: the whole batch is refused unless the balance covers 8 credits per URL (any URL *could* be a hit). So no API call is ever spent on a lookup that can't be billed, and a user low on credits is told to top up or connect their own key. If the user has connected their own Airscale key (BYO, via the integrations page), lookups run against that account instead — no Sliq credit gate and no Sliq credit charge.</summary> <returns> <description>A list of result dicts in input order. Per hit: `{status: 'success', found: True, phone_number, phone_numbers, provider, linkedin_url, credits_charged: 8}` (0 on the BYO path) — `phone_number` is the first number, `phone_numbers` the full list. Per miss: `{..., found: False, phone_number: None, phone_numbers: [], credits_charged: 0}`. A malformed (non-LinkedIn) URL or an upstream failure on one URL becomes a per-item `{found: False, error, credits_charged: 0}` in that slot — it never aborts the rest of the batch. If the up-front worst-case credit check fails, it raises `InsufficientCreditsError` (no lookups are attempted).</description> </returns>

  ConnectorOAuth

• update_linkedin_channel_settingsA

  Metadata MCP ConnectorA

  Update the LinkedIn channel settings of an existing DRAFT wizard campaign: native objective, bidding optimization goal (including Reach), bid strategy with manual bid amount, and the LinkedIn conversion actions the campaign optimizes toward. These are the settings the platform UI shows in the LinkedIn channel drawer of the campaign draft page (Native Objective, Bidding Optimization Goal, Bid, Conversion Actions). The campaign MUST already have its LinkedIn channel enabled (via create_campaign / add_and_edit_campaign_elements with a `linkedin` block). WARNING: DRAFT-ONLY: the platform rejects these edits once the campaign is Launching/Launched. KEYWORDS: linkedin, linkedin campaign, linkedin settings, campaign settings, draft campaign, objective, native objective, brand awareness, website visits, engagement, video views, bidding optimization goal, optimization goal, reach, impressions, landing page clicks, engagement clicks, bid, bid strategy, auto bid, manual bid, maximum delivery, conversion, conversions, conversion actions, conversion tracking, insight tag, settings WHEN TO USE: - Set the LinkedIn native objective (e.g. Brand Awareness instead of the default Engagement) - Optimize a Brand Awareness campaign for REACH instead of IMPRESSIONS - Switch between auto bid (LinkedIn maximum delivery) and a manual bid - Pick which LinkedIn conversion actions the campaign optimizes toward and reports on PARAMETERS (campaign_id required; everything else optional, and an unspecified setting keeps its current value on the channel): - campaign_id: the wizard campaign ID - objective: BRAND_AWARENESS | WEBSITE_VISIT | ENGAGEMENT | VIDEO_VIEW, the LinkedIn native objective. Only selectable on Brand Awareness (CTR) campaigns: a Lead Gen (CPL) campaign derives it from its offer at launch (lead-gen form -> LEAD_GENERATION, landing page -> WEBSITE_CONVERSION). The platform default for a new LinkedIn channel is ENGAGEMENT. Every ad already on the channel must be supported by the objective (VIDEO_VIEW is video-only, MESSAGE ads only fit WEBSITE_VISIT, DOCUMENT ads lock the objective, a video-only channel accepts only ENGAGEMENT or VIDEO_VIEW). A channel holding CTV ads is always Brand Awareness / Reach at launch and cannot be changed here. Changing the objective also resets the cost type and the bidding optimization goal to the objective's default (BRAND_AWARENESS -> IMPRESSIONS, WEBSITE_VISIT -> LANDING_PAGE_CLICKS, ENGAGEMENT -> ENGAGEMENT_CLICKS, VIDEO_VIEW -> VIDEO_VIEWS), so pass bidding_optimization_goal in the same call when you want something else. - bidding_optimization_goal: what LinkedIn optimizes delivery for. Allowed per objective: BRAND_AWARENESS -> IMPRESSIONS | REACH; WEBSITE_VISIT -> LANDING_PAGE_CLICKS | IMPRESSIONS; ENGAGEMENT -> ENGAGEMENT_CLICKS | IMPRESSIONS; VIDEO_VIEW -> VIDEO_VIEWS | IMPRESSIONS. Conversation and Message ads are always IMPRESSIONS. CTR campaigns only. - bid_strategy: AUTO_BID (LinkedIn "maximum delivery", what the campaign builder applies by default) or MANUAL_BID (needs bid_amount). CTV ads REQUIRE AUTO_BID; Spotlight and Text ads REQUIRE MANUAL_BID. - bid_amount: manual bid in the account currency, used only with MANUAL_BID. - conversion_action_ids: ids of LinkedIn conversion actions (from list_linkedin_conversions) the campaign should optimize toward and count as conversions: website visits, URL-rule page views, lead form fills. REPLACES the current selection; pass [] to clear it (the campaign then falls back to the account's default Insight Tag URL match). Every id must exist and be enabled on the connected LinkedIn account, or launch validation fails. NOTE: the platform UI only shows this picker for campaigns with landing-page offers and an objective other than Brand Awareness; ids stored outside that case are still sent to LinkedIn at launch, but that path is not exercised by the UI. NOT SETTABLE ANYWHERE IN THE PLATFORM (say so instead of promising them): LinkedIn Audience Network on/off and its category exclusions, audience expansion (campaigns always launch with expansion OFF), frequency caps, Thought Leader ads. LinkedIn geo targeting is not a channel setting either: it lives on the audience / target group. EXAMPLES: Brand Awareness optimized for Reach on auto bid: update_linkedin_channel_settings({"campaign_id": 12345, "objective": "BRAND_AWARENESS", "bidding_optimization_goal": "REACH", "bid_strategy": "AUTO_BID"}) Track two conversion actions on a Website Visits campaign: update_linkedin_channel_settings({"campaign_id": 12345, "conversion_action_ids": ["123456", "234567"]}) RESPONSE: {success, campaign_id, channel_id, campaign_status, campaign_goal, channel_ad_types, applied:{...}, errors?}. `applied` echoes exactly what was pushed to the platform. INTEGRATION WITH OTHER TOOLS: - list_linkedin_conversions lists the conversion actions available on the account - search_campaigns_by_names / get_campaign_by_wizard_id to find the campaign - The LinkedIn channel is enabled by create_campaign or add_and_edit_campaign_elements - check_campaign_launch_readiness validates the result before launch

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  Destructive

  API key

• create_update_document_adA

  Metadata MCP ConnectorA

  Create a new or update an existing LinkedIn Document Ad on the Metadata platform. A LinkedIn Document Ad promotes a multi-page document (a PDF — e.g. a whitepaper, ebook, report, or guide) natively in the LinkedIn feed. Members preview the first few pages inline, then unlock the full document (typically gated behind a lead form). It is LinkedIn-only. IMPORTANT: This tool is ONLY for LinkedIn Document Ads (channelType=LINKEDIN, adType=DOCUMENT). For IMAGE/GIF ads use create_update_image_ad; for VIDEO ads use create_update_video_ad; for CONVO use create_update_convo_ad; for Sponsored Messaging use create_update_linkedin_message_ad. BEHAVIOR: - If `id` is NOT provided -> creates a new Document Ad. - If `id` IS provided -> updates the existing Document Ad with that ID. CREATIVE WORKFLOW (MUST DO BEFORE CALLING): 1. The document must already exist in the creative library as a DOCUMENT asset. Find it with `search_library_creatives_by_name(contentTypes="DOCUMENT")`, or confirm a specific id with `fetch_creative_details`. 2. Pass that asset's integer id as `libraryId`. It MUST be a DOCUMENT-type creative — an image or video id will be rejected by LinkedIn. Unlike IMAGE/VIDEO ads there is NO display URL: the gated document is the destination, so no link field is accepted. CHARACTER LIMITS (mirror the LinkedIn ad limits the platform UI enforces): - name <= 50 chars (ad name in the library) - headline <= 200 chars (the headline shown with the document) - text <= 3000 chars (the introductory text) INPUT PARAMETERS: - id (optional): Existing Document Ad ID. Provide to UPDATE; omit to CREATE. - name (required, <= 50): Ad name in the library. - libraryId (required): Integer id of the DOCUMENT creative in the library (contentType=DOCUMENT). NOT an image/video id. - headline (required, <= 200): Headline shown with the document. - text (required, <= 3000): Introductory text shown with the document. - ctaType (optional, default UNLOCK_FULL_DOCUMENT): the call-to-action. UNLOCK_FULL_DOCUMENT is the document-gate CTA. - maxPreviewPages (optional, default 1): how many pages of the document are previewable before the unlock gate. Positive integer. - completionStatus (optional, default DRAFT): "DRAFT" or "COMPLETED". Use COMPLETED only when every required field is final. WHEN TO USE: - User asks to "create a LinkedIn Document Ad" / "whitepaper ad" / "promote a PDF / ebook / report on LinkedIn". - User wants to update an existing Document Ad. WHEN NOT TO USE: - Feed image / GIF ad -> create_update_image_ad - Feed video ad -> create_update_video_ad - Branching conversation flow -> create_update_convo_ad - One-shot Sponsored Message -> create_update_linkedin_message_ad EXAMPLE USAGE (Create): create_update_document_ad( name="Q3_Whitepaper_LI_Document", libraryId=15791, headline="The 2026 State of B2B Marketing", text="Download our latest research on pipeline attribution.", maxPreviewPages=2, ) EXAMPLE USAGE (Update): create_update_document_ad( id=29144, name="Q3_Whitepaper_LI_Document_v2", libraryId=15791, headline="The 2026 State of B2B Marketing (Updated)", text="Now with fresh benchmarks.", ) COMMON MISTAKES: - Passing an IMAGE/VIDEO libraryId — the asset must be a DOCUMENT (use search_library_creatives_by_name(contentTypes="DOCUMENT")). - Passing a display / landing URL — Document Ads have no link field. - Using this tool for a non-LinkedIn channel — Document Ads are LinkedIn-only.

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• call_write_toolA

  Opus Growth, Ad Platforms MCP ConnectorA

  Run a WRITING Opus tool by name (create / update / pause / remove) — the gateway to every write capability that is not in your visible core set. Use search_tools(query) FIRST to get the exact name and its argument schema, then call it here. name = exact tool name; arguments = that tool's parameters as an object. Writes go to the advertising platform APIs the user has connected (Google Ads, Microsoft Advertising, Meta, TikTok, LinkedIn) and to Opus Growth's own hosting/WordPress services. Read-only tools are refused here — use call_tool for those. The tool's own preview-and-confirm gate still applies: tools that change a live account return a PREVIEW with confirm=false and only apply with confirm=true. Credits and access rules behave exactly as calling the tool directly.

  Connector

  Destructive

  OAuth

• campaignstack_request_connect_linkA

  campaignstackA

  A link the user clicks to connect a NEW LinkedIn or Google account. Connecting is a browser step by design: LinkedIn needs a session the extension captures, Google needs its consent screen, and neither a cookie nor a password should ever be pasted into a chat. For LinkedIn the link is the accounts page (with the extension the connect is one click; without it, an email and password or a session cookie entered on that page). For Google the link is a consent URL minted for this user, valid ten minutes. Send the link, then poll campaignstack_list_accounts until the account appears, and link it to the right workspace with campaignstack_link_account_to_workspace if it is not there already. Never ask the user for their credentials.

  ConnectorAPI key

• linkedin_adsA

  Adako: Google Ads, Meta Ads & Linkedin Ads MCPA

  Reads and tool lookup for LinkedIn Ads; nothing called here changes anything. The 17 LinkedIn Ads tools that change something run through linkedin_ads_write. Naming: these tools use LinkedIn API names. Since October 2025 Campaign Manager calls a campaign group a "campaign", a campaign an "ad set" and a creative an "ad", so campaign_group_id is what the user sees as a campaign and campaign_id is an ad set. When the user says "campaign", check which level they mean (linkedin_get_campaign_structure shows both), and answer in the words Campaign Manager uses. linkedin_ads(action="execute", tool_name="…", arguments={...}). action="list_tools" (the write half included) and action="get_tool_schema" are free; never guess a tool_name. accounts=["…","…"] or accounts="all_active": one read across up to 20 LinkedIn Ads accounts, free like every read. Not in this router, called by name: linkedin_get_campaign_performance (linkedin campaign (ad set) performance). Tools by category: **analysis** linkedin_analyze_creative_performance, linkedin_analyze_wasted_spend **targeting** linkedin_estimate_audience_size, linkedin_forecast_campaign_supply, linkedin_search_targeting **discovery** linkedin_explain_objectives, linkedin_get_organizations **audiences** linkedin_get_audience_insights **structure** linkedin_get_campaign_structure, linkedin_list_campaign_groups, linkedin_list_campaigns, linkedin_list_creatives **performance** linkedin_get_creative_performance **reporting** linkedin_get_engagement_metrics **conversions** linkedin_list_conversions **assets** linkedin_validate_assets

  ConnectorOAuth

• linkedin_resolve_urlA

  Veezee: LinkedIn people & company data for agentsA

  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.

  ConnectorOAuth

• search_webA

  LinkedIn MCP Server (Salesbot)A

  General-purpose Google search — returns organic results for any query. Unlike search_google_xray (LinkedIn-only), this searches the entire web. Useful for finding job postings on portals (jobs.cz, prace.cz, profesia.sk, indeed.com), company info, news, or any other web content. Results are NOT saved to contacts — use this for research and discovery. Capped at 4 calls per minute to protect the Serper/Google budget.

  ConnectorNo auth

• get_connection_detailsA

  YouSpotA

  Get the full profile for one of the user's LinkedIn connections: work history, education, skills, and their About summary. Use this after search_connections when you need depth on a specific person. Identify them by name, or by linkedin_url for an exact match. A found:false response carries the user's imported-connection count: if no_imported_data is set, nothing was searched, so report the missing import rather than a missing person.

  ConnectorNo auth