"A platform for finding people on LinkedIn" matching MCP tools:

• connect_domainA

  LayeroA

  Connect a custom domain to a site. IMPORTANT: between this call and a working domain stands A PERSON. You get DNS records — show them to the user and explain they go in at their domain registrar. Do not wait for readiness: DNS propagates in minutes to an hour, the platform re-checks on its own, and you check later via `check_domain`. Spinning here burns time and context for nothing. The address can be passed as-is: the platform reduces `https://shop.example.com/page` to `shop.example.com` itself.

  ConnectorOAuth

• bulk_scheduleA

  SendItB

  Schedule multiple posts at once from CSV content. USE THIS WHEN: • User has a spreadsheet or list of posts to schedule • Planning a content calendar for a month • Migrating content from another tool CSV FORMAT (required columns): • platform: linkedin, instagram, x, tiktok, threads • scheduled_time: ISO 8601 format (e.g., 2024-02-15T10:00:00Z) • text: Post content/caption OPTIONAL COLUMNS: • media_url: Image or video URL • first_comment: First comment to add (Instagram/LinkedIn) • hashtags: Additional hashtags to append PROCESS: 1. First call with validate_only: true to check for errors 2. Review validation report with user 3. Call again with validate_only: false to execute import

  ConnectorNo auth

• connect_domainA

  LayeroA

  Connect a custom domain to a site. IMPORTANT: between this call and a working domain stands A PERSON. You get DNS records — show them to the user and explain they go in at their domain registrar. Do not wait for readiness: DNS propagates in minutes to an hour, the platform re-checks on its own, and you check later via `check_domain`. Spinning here burns time and context for nothing. The address can be passed as-is: the platform reduces `https://shop.example.com/page` to `shop.example.com` itself.

  ConnectorAPI key

• attach_to_outreachA

  SliqA

  <summary>Attach a file from the user's library to a queued outreach email or LinkedIn message. Only attach when the user explicitly asks to attach a specific file to someone's message — never on your own initiative. attachment_id comes from list_attachments. Name the queued message by exactly one handle: recipient_email for a queued email (pending or awaiting approval); target_provider_id for a queued LinkedIn message, or target_identifier for one whose profile is still resolving — both as shown on the row in manage_linkedin_invite_queue's status read. On LinkedIn only messages carry files, not connection requests or InMails, and LinkedIn takes fewer file types than email; a file the channel can't send is refused with the reason. The same file can be attached to several messages.</summary> <returns> <description>The attached file's name and every file now on that message, shaped `{'attached': True, 'filename', 'attachments': [{'id', 'filename', 'mime_type', 'size'}]}`.</description> </returns>

  ConnectorOAuth

• gtm_update_playA

  GTM OttoA

  Change a play's own knobs — name, goal, voice — its two switches, and the ACCOUNT's pacing (daily action cap, working hours: shared by every play on the LinkedIn account, not per play). `paused: true` is the human's stop button (nothing runs, nothing is sent); `paused: false` resumes. `status: 'active'` LAUNCHES a draft; `status: 'draft'` takes it back off the road. Seat rule, enforced server-side: no live LinkedIn seat ⇒ neither launch nor resume makes it active — it stays/falls back to draft and the note says so. Launching or resuming kicks the play's due lanes at once. Only launch, resume or raise the cap when the human asked for it in this conversation: an active play spends the month's lead quota and acts from the human's own LinkedIn account. Does not touch the autonomy ladder.

  Connector

  Destructive

  No auth

• monitoring_create_monitorA

  Manifold MCPA

  Sets up a monitor: a check Manifold repeats on a schedule, keeping each result so it can report what changed. Urgent changes reach the user as an email alert. Show the monthly cost from preview first, then create it once the user agrees. Give it a description saying why the user wants it, so an agent reading its changes later knows what to do with them. Use when: "monitor this every week", "keep an eye on X", "tell me when Y changes", "check Z every hour", or the user ran the same check by hand before and wants it repeated. Not for: a one-off look, call the tool itself (reddit_search_posts, seo_get_page, seo_get_position, ads_get_advertiser_ads). Reading what a monitor found, use monitoring_get_changes. Returns: Record. monitor (monitor_id, name, description, preset, status, cadence, fields, est_credits_check, est_credits_month, next_check_at), created (false on preview). The first check runs within five minutes and records a starting point; changes are reported from the second check on. Fields by preset: mentions {keywords (up to 10), platforms (reddit, linkedin, instagram, tiktok, youtube; default reddit), communities (Reddit, every new post read in full), pages (1 to 3 per community per check)}, where Instagram searches each keyword as one hashtag ("acme crm" reads #acmecrm), so use a keyword people tag; social_accounts {accounts [{platform (twitter, linkedin, instagram, tiktok, youtube, facebook), account (handle, or URL for facebook and linkedin)}] (1 to 10)}; reviews {items [{source app_store or google_play, app_id} or {source google_maps, place_id or cid} or {source google_shopping, product_id, gid}] (1 to 5), stars, location}; website_changes {pages (1 to 10 URLs), mode (new_items: new links under the page and prices; any_change: new text), words}; ads {brands (1 to 5, a website works best), platforms (facebook, google, linkedin, tiktok)}; google_rankings {site, keywords (1 to 50), location}; ai_visibility {brand, aliases (other names for the brand, up to 5), domain (the brand's site, for citation share), questions (1 to 25; ones that name the brand are counted apart), competitors (up to 9), engines, samples (1 to 3), location, language}. cadence is hourly, daily or weekly; checks repeat from the first one. A bad field is InvalidTarget naming it. Cost: 0 credits to create. Each check charges for the calls it makes at their own prices, shown as est_credits_check and est_credits_month. Monitor checks read live data, never the cache. Example: {"preset": "mentions", "fields": {"keywords": ["acme crm"], "platforms": ["reddit", "linkedin"]}, "description": "Threads asking for a CRM, to answer while they are fresh.", "preview": true}

  ConnectorAPI key

• request_task_quoteA

  Molt2MeetA

  ESCROW FLOW ONLY. Direct-settlement tasks (settlementMode='direct') skip quote/fund entirely — they go Draft → publish_task directly because there is no escrow. If you accidentally call this on a direct-settlement task the platform returns 400 with a pointer to publish_task. Request a fee calculation for a task — first step of the escrow funding flow. Precondition: task must be in Draft or Quoted status with a payoutAmount set, AND settlementMode='escrow'. Calling this on an already-funded task returns an error. Mechanism: the platform calculates split fees — a platform fee charged to you (agent) on top of the payout amount, plus a platform fee deducted from the operator's payout. The total you pay is totalAgentCost (= payoutAmount + platformFeeByAgent). Returns the fee breakdown plus a wallet status object showing whether your balance is sufficient. Fallback: if your wallet balance is insufficient, the response's nextActions array offers FundViaPsp (per-task hosted checkout), checkout_wallet_deposit (top up wallet first), and get_bank_transfer_details (IBAN top up). Pick whichever matches your funding pattern. Next: fund_task with the chosen fundingMethod, then publish_task. Requires authentication.

  ConnectorNo auth

• send_linkedin_messageA

  Salesbot - B2B outreach LinkedIn MCP Server with CRM and emailA

  Send a one-off LinkedIn message to a specific saved contact outside any campaign. Prefer contact_id; Salesbot resolves the LinkedIn identifier internally. A random delay, daily/hourly limits, allowed hours and human approval are enforced. Refused with code DUPLICATE_RECENT_MESSAGE (and the campaign name + date) when a campaign of this LinkedIn account already messaged the person within the last 30 days; to continue an existing conversation use reply_to_chat.

  ConnectorAPI key

• social_searchA

  socialbridge-mcpA

  Search a single network for posts matching a query, returned as the unified Post[] schema and tagged with its platform. Keyless on TikTok, YouTube, and Pinterest. Instagram, Twitter/X, Reddit, and Facebook need operator-side credentials (returns credentials_required until set). Snapchat and Threads do not support keyless search (returns not_supported); LinkedIn is quarantined. To fan one query across every network at once, use search_all.

  ConnectorNo auth

• delete_graph_objectsA

  YouSpotB

  Delete EVERY object of one type from the user's graph, however many there are: what to reach for when they ask to clear out a whole category ('delete all my HubSpot contacts') rather than one record. Pass import_id instead to delete everything one import added (its contacts, companies, notes and files, the uploaded file and the import itself); imports are graph objects of type 'import_run'. Pass source 'linkedin_import' instead to delete every connection a LinkedIn export loaded and the people made from them. Deleting one object is delete_graph_object instead. This delete is permanent, and at this scale it is the only kind that helps: a synced portal can be millions of records. Use only when the user explicitly asked for these to go, never on your own initiative, and name one type, import or source per call. In chat this tool deletes nothing: it counts the records and returns what to tell the user, and their click starts the deletion.

  Connector

  Destructive

  No auth

• linkedin_analyticsA

  YouSpotB

  The user's LinkedIn post analytics from LinkedIn's own API (their connected account) — impressions, unique members reached, reactions, comments, and reshares. Use for questions like 'how many impressions did I get last month?' or 'how are my posts performing?'. Omit dates for lifetime totals; pass start_date/end_date for a window; set daily=true (with one specific metric) for a per-day series to describe trends. Numbers are live from LinkedIn, unlike get_my_linkedin_posts whose per-post counts come from a periodic sync.

  ConnectorNo auth

• sync_linkedin_connectionsA

  Salesbot - B2B outreach LinkedIn MCP Server with CRM and emailA

  Synchronize one provider-safe page (at most 500) of the API-key owner's 1st-degree LinkedIn relations into the local workspace cache. This is a provider read, not a LinkedIn people search, and does not consume the search quota. The server persists continuation state and atomically enforces a 15–20 minute delay, four-page hourly cap, and twelve-page daily cap across UI and MCP. Respect RELATIONS_SYNC_PROTECTED retry_after_seconds before continuing.

  ConnectorAPI key

• fetch_post_engagersA

  SliqA

  <summary>Fetch the people who reacted to or commented on a LinkedIn post — the user's own post or anyone else's — and store them as queryable engagement rows. Use when the user wants to turn a post's engagers into leads ("everyone who liked this post", "who commented on her launch post"). Visibility follows the user's LinkedIn account: any post it can view works, and private or deleted posts return a plain error. The list is capped at 500 reactions + 500 comments per post; on a bigger post the return flags the cut-off. Data fetched within the last 6 hours is served from the database at no cost; loading a post Sliq hasn't tracked yet counts one against the user's daily LinkedIn post-read budget. A post with hundreds of engagers takes around half a minute — set that expectation with the user before calling this on a big post. When this runs in an agent, every person who engaged is saved as an `agent_search_results` person row, rendered in the agent's Output tab and queryable via `query_search_results`: `data.person` carries the name and headline, `linkedin_provider_id` and `linkedin_url` the LinkedIn handles, and `data.columns` the engagement (Engagement, Comment, Post, Post URL). Company pages that reacted or commented aren't people, and the user isn't a lead, so neither is saved; both stay in the engagement rows. Re-running updates existing rows rather than duplicating them. Pass `list_name` to name their list; absent, they land in the 'default' list. Each person new to the list is checked against `criteria`, one at a time, reading their headline and engagement, and saved with the verdict; the rejected ones are hidden from the list's default view and from `query_search_results`. The check adds about 20 seconds per hundred people. To keep everyone who engaged, write broad criteria, such as "Anyone who engaged with this post". A person already on the list keeps their verdict, so to screen a post's engagers against new criteria, pass a new `list_name`. After this returns, read the saved people with the `query_search_results` call in `next_step`, which is scoped to this post: one list can hold several posts' engagers. Judge anyone the check kept as `unclear` or left without a verdict yourself, then queue outreach for the people who fit with one batched `queue_linkedin_outreach` call passing each row's `linkedin_provider_id` as `provider_id` and its `linkedin_url` as `linkedin_url`. Send-time resolution skips anyone already connected, so they don't need pre-filtering here. Every engager, the rejected ones included, also stays queryable with `query_linkedin_post_engagements` using `post_id = <post_analytics_id>`.</summary> <returns> <description>On success, a dict {'success': True, 'post_analytics_id': int, 'author_name': str, 'is_own_post': bool, 'post_text_snippet': str, 'from_cache': bool, 'reactions_stored': int, 'comments_stored': int, 'unique_engagers': int, 'truncated': bool, 'budget': {'used_today': int, 'limit': int}, 'engagers_preview': [first 10 engagers, unchecked], 'next_step': str, 'list'?: {'list_name', 'created', 'updated', 'total', 'rejected'}}. `unique_engagers` counts company pages too; `list.total` counts only the people saved, rejected ones included, so it can be lower. `list.created` and `list.updated` count the people the list shows, and `list.rejected` the ones the check turned down. `budget` is today's LinkedIn post-read budget. On failure, {'success': False, 'error': str} when the post isn't visible to the user's account, the daily LinkedIn post-read budget is spent, or LinkedIn actions are paused after a rate limit.</description> </returns>

  ConnectorOAuth

• edit_monitor_membersA

  SliqA

  <summary>Add and/or remove watched people or company pages on an existing `list`-mode LinkedIn monitor, incrementally — you pass only the profiles that are changing, never the whole list. `add` and `remove` are LinkedIn profile URLs or vanity slugs for people, and full `linkedin.com/company/...` URLs for company pages (a bare company name or slug is read as a person's slug). A swap is one call (`add=[new]`, `remove=[old]`). Both forms of one profile (full URL and bare slug) collapse to a single watched member, so re-adding someone already watched is a no-op. The change takes effect on the monitor's next scheduled run. Use this instead of re-running `set_up_linkedin_monitoring` whenever the user just wants to tweak who's watched ("also watch Bob", "drop Alice"): setup would force re-passing every existing member, and since each watched profile is billed per run, one dropped URL on the re-echo silently stops watching that person. To change schedule, voice, or the action flags, use `set_up_linkedin_monitoring` (members are preserved there when omitted); adding the very first members or resetting the whole list is setup too.</summary> <returns> <description>Dict with status ('active'), name, members_count, added, removed, unresolved, and message.</description> </returns>

  ConnectorOAuth

• add_lead_finder_prospectsA

  EmailchaserA

  SPENDS CREDITS, AND BY DEFAULT METERED EMAIL VERIFICATION. Adds people from the Lead Finder contact database to a campaign as leads, revealing their contact details, in the background. Pass refs (from search_lead_finder results; up to 1,000 different people by default) to add exactly those people, or pass filters and count (1 to 5,000 by default) to add count people matching the filters who are not in the workspace yet. A filters add always walks the matches from the top and skips anyone already a lead, free and not counted, so repeating the same add adds the NEXT count people and charges again. Never repeat an add to retry: after an error or a timeout, call list_lead_finder_imports to see whether it started. A filters add stops early when the audience runs out or once it has looked at five people for every one requested (at least 1,000). People already added count toward that limit even though skipping them is free, so after an add of more than about 1,000 people a small follow-up can stop with nobody added. Every person a filters add looks at, added or skipped, also uses the account's daily allowance for filters adds (25,000 people by default). Each person added costs 1 credit ($0.033 at list), reported as creditsPerProspect; the response reports estimatedCredits, the most the add can cost in credits, and the wallet must hold that much for it to start. People already in the workspace, blocklisted, without a usable address, on a personal mailbox when the campaign only takes business addresses, or marked invalid by verification are skipped and cost no credits. verifyEmails (on by default) checks every screened address with the paid email verification waterfall, including the ones it marks invalid: one or two checks per address, billed as metered usage on the next invoice (price per check: GET /email-verification/rates in the REST API), within the account's monthly verification spend limit. Catch-all and unconfirmed addresses are added and charged, and so is every address once that limit is reached; verification.limitReached and verification.unknown on get_lead_finder_import count them. Leads added to a running or paused campaign get their emails at once (a paused campaign sends them when resumed); adding to a completed campaign resumes it, so it starts sending again; in a draft campaign the emails are created at launch. At most 3 adds run at once in a workspace. A refusal names its reason, and a 429 also says when to retry (reason running_imports, daily_import_limit, daily_budget, monthly_budget or fair_use_floor). Poll get_lead_finder_import with the importId until finishedAt is set. Check get_credit_balance first; buy credits with purchase_credits.

  ConnectorNo auth

• merge_crm_companiesA

  Salesbot - B2B outreach LinkedIn MCP Server with CRM and emailA

  Merge a duplicate CRM company into another one (e.g. 'Škoda JS' into 'Škoda Group'). All people move to keep_crm_company_id, empty details are filled from the duplicate, account notes are joined, the duplicate's name is remembered as an alias so future leads with that name land in the kept company, and the duplicate is deleted. Cannot be undone — only merge when both records are clearly the same organisation (check with get_crm_company), and confirm with the user when unsure. Prefer keeping the company imported from LinkedIn.

  Connector

  Destructive

  API key

• get_segment_funnelA

  SliqA

  <summary>One campaign's lead funnel split by a segment group's tags, as the campaign's Summary shows it when the user filters it by tag — "how are VPs doing on this campaign", "which seniority replies best here". It counts each person on the campaign once, so on a campaign that uses both channels its rates can differ from get_segment_rates, which scores each channel separately. Quote the funnel's stage counts from `funnel.reached`, the numbers on the Summary's rungs: per rung, everyone who got at least that far, except Accepted, which counts the people who accepted a connection request the campaign sent them, out of `funnel.invited`, the people sent one. The funnel's other stage keys count only the people currently at that stage. Quote the funnel's percents from `funnel.rates` and `funnel.step_rates` rather than dividing its counts. No filter lists Accepted's people. To list any other rung's people, call list_people with this agent_id, segment_group_id set to `selected.group_id`, a "segment" filter for the tag name and a "reached" filter for the rung.</summary> <returns> <description>Dict with the segment groups, the chosen group's per-tag funnels, and the per-person tagging rate, {groups, selected, credits_per_person}. `groups` lists the segment groups that tag the user's prospects as {id, name, mode, tags: [{id, name}], covers, classify_running}: `covers` is whether the group tags this campaign's people, new ones included (automatically, within about 15 minutes of their profile lookup or first contact, so a covering group needs nothing set up to stay current), and `classify_running` whether a tagging run is going. `selected` is null when group_id is omitted and no group covers the campaign; else {group_id, everyone, tags, not_tagged, out_of_credits}. `everyone` and each `tags` entry ({tag_id, tag, ...}) carry `funnel` (the campaign summary's lead_funnel shape: `reached` {contacted, accepted, replied, interested, meeting_booked}, the per-stage people counts, `invited`, reply_rate and accept_rate, and `rates` {accepted of invited; replied, interested, meeting_booked of contacted} and `step_rates` {interested of replied, meeting_booked of interested} as whole percents, null where the base is 0), `contacted` (people reached) and `signal` ('thin' under 10 contacted, 'early' under 30, else 'solid'). A last entry with tag_id null and tag 'No match' holds people the classifier couldn't place; a person with several tags counts under each. `not_tagged` counts contacted people not tagged yet, and `out_of_credits` is true when they are waiting on a credit top-up.</description> </returns>

  ConnectorOAuth

• set_lead_inputA

  PumpGTM MCP serverA

  Store a value the customer supplies for one person, such as a link to a video they recorded, so a LinkedIn message, email, X DM or Instagram DM step declared with tool customer_input can send. Identify the person by exactly one of leadId, LinkedIn profile URL, email address or X handle. values maps the sequence's token names (for example video_url) to the customer's text; the key comes from the sequence, the customer never types it. One call fills every step of that person's sequence that uses the token and has not sent yet. A LinkedIn message, opted-in email or X DM step may instead ask for a file for each person (tool customer_input attachment, for example a personalised demo video). Limits are the providers': LinkedIn 15 MB per message together with the step's own files; email one document, image or MP4 up to 18 MB (1.5 MB from Microsoft mailboxes); X one image up to 5 MB, GIF up to 15 MB or MP4 video up to 50 MB and 140 seconds. Nothing is compressed: a larger file is refused with the limit and the way forward, which you relay as written (compress it and try again, or send a video link instead). A link to a video (Loom, YouTube, Drive) is a text value such as video_url, not a file. To send a file, call once with upload { key, fileName, size } to get a one-time uploadUrl, PUT the file's bytes there with the returned headers, then call again with files { key: uploadTicket }; if you cannot upload bytes yourself, give the customer the returned appUrl to add the file in the app instead. For several people at once (the customer has already decided which file is whose; do not second-guess their pairing), call with uploads [{ leadId or linkedinUrl or email or xUsername, key, fileName, size }] (up to 25, no top-level person) to get one uploadUrl and uploadTicket per person, PUT each file, then call with confirmUploads [uploadTicket, ...] to attach them all. Each person succeeds or is refused on their own with a reason; tickets last two hours and confirming one again is harmless, so a rerun only adds what is missing. Afterwards list_leads with sequenceId and personalFiles=true shows which file each person has. Nothing is sent in this call: the paced engine sends on its next run if the person is at that step, or when they reach it. A value or file for someone who already replied, finished, or already received that message is refused with nothing changed. The result includes how many people in that sequence are still waiting. Open world: the stored value releases a held message to that person, a third party.

  ConnectorOAuth

• set_lead_inputA

  PumpGTMA

  Store a value the customer supplies for one person, such as a link to a video they recorded, so a LinkedIn message, email, X DM or Instagram DM step declared with tool customer_input can send. Identify the person by exactly one of leadId, LinkedIn profile URL, email address or X handle. values maps the sequence's token names (for example video_url) to the customer's text; the key comes from the sequence, the customer never types it. One call fills every step of that person's sequence that uses the token and has not sent yet. A LinkedIn message, opted-in email or X DM step may instead ask for a file for each person (tool customer_input attachment, for example a personalised demo video). Limits are the providers': LinkedIn 15 MB per message together with the step's own files; email one document, image or MP4 up to 18 MB (1.5 MB from Microsoft mailboxes); X one image up to 5 MB, GIF up to 15 MB or MP4 video up to 50 MB and 140 seconds. Nothing is compressed: a larger file is refused with the limit and the way forward, which you relay as written (compress it and try again, or send a video link instead). A link to a video (Loom, YouTube, Drive) is a text value such as video_url, not a file. To send a file, call once with upload { key, fileName, size } to get a one-time uploadUrl, PUT the file's bytes there with the returned headers, then call again with files { key: uploadTicket }; if you cannot upload bytes yourself, give the customer the returned appUrl to add the file in the app instead. For several people at once (the customer has already decided which file is whose; do not second-guess their pairing), call with uploads [{ leadId or linkedinUrl or email or xUsername, key, fileName, size }] (up to 25, no top-level person) to get one uploadUrl and uploadTicket per person, PUT each file, then call with confirmUploads [uploadTicket, ...] to attach them all. Each person succeeds or is refused on their own with a reason; tickets last two hours and confirming one again is harmless, so a rerun only adds what is missing. Afterwards list_leads with sequenceId and personalFiles=true shows which file each person has. Nothing is sent in this call: the paced engine sends on its next run if the person is at that step, or when they reach it. A value or file for someone who already replied, finished, or already received that message is refused with nothing changed. The result includes how many people in that sequence are still waiting. Open world: the stored value releases a held message to that person, a third party.

  ConnectorOAuth

• leads_search_peopleA

  Manifold MCPA

  People matching title, seniority and company filters. No email. Use when: "find heads of marketing at fintech startups", building a target list by role, prospecting by ICP. Not for: someone to email at a specific website about a link, use leads_get_domain_emails (keyed by domain). One person's full record, use leads_get_person. An email for a named person, use leads_get_email. Returns: List. rows[]: id (the LinkedIn profile URL; null when the person has no profile, so look them up by name and domain), first_name, last_name, headline, title, title_start (YYYY-MM, so time in the role), company, company_domain, company_id, company_linkedin_url, company_employees, company_industry, location, linkedin_url. rows_available is the provider's total. Give at least one of titles, seniority, company_domains, industries, locations or keywords. A page holds at most 100 rows whatever the limit; page on with meta.cursor. Cost: 12 credits per 100 rows asked for (limit), rounded up. Default 12 credits. Cached 7 days. Example: {"titles": ["head of marketing"], "industries": ["fintech"], "locations": ["London"], "limit": 50}

  ConnectorAPI key

• tiktok_get_profileA

  Manifold MCPA

  One TikTok account: its follower count, its lifetime likes and how many videos it has posted. Use when: sizing a creator or a brand on TikTok, checking a handle is real, reading a bio before outreach. Not for: the account's videos, use tiktok_get_videos. Where its audience is, use tiktok_get_audience. Finding accounts by topic, use tiktok_search_videos and read the authors. Returns: Record. The account's handle, name, bio, verified, followers, following, posts_count, likes, views, website (the link in bio) and links, with other profile fields where TikTok fills them. null or empty = the platform does not publish it. Cost: 1 credit. Cached 24 hours. Example: {"handle": "@gymshark"}

  ConnectorAPI key