MimikFlow
Launch B2B prospecting
- Category
- Pending
- Primary Subcategory
- Pending
Integration details
Description
MimikFlow helps existing customers launch and manage automated B2B prospecting from their AI assistant. They can review results and conversations, handle drafts and escalations, adjust campaign settings, and add selected prospects while MimikFlow preserves the account's plan, permissions, and outreach safety limits.
- Integration type
- Plugin
- Verification status
- Not applicable
- Platform
- ChatGPT
- Category
- Pending
- Primary Subcategory
- Pending
- Secondary Subcategories
- None listed
- Brand
- Unknown
- Access
- Account required
- First tracked
- 2026-09-03
- Tool count
- 34
- Geography
- US
The broad Category that contains the Primary Subcategory.
The Primary Subcategory used for this profile’s headline score.
Other Subcategories where the Integration is listed.
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Competitive lineup
34 tools agents can invoke
Queue LinkedIn profile URLs into the user's prospecting machine. Each profile is fetched, evaluated against the campaign's ideal customer profile (filter_mode 'icp'; 'all' skips the filter; 'custom' uses custom_filter_instructions), deduped against existing leads, and good prospects become new leads that MimikFlow then engages automatically (invite, personalized DM, follow-ups, AI conversation) at its normal LinkedIn-safe pace. Runs in the background. Accepts URLs from search_prospects or any other source (CRM export, spreadsheet, webinar attendee list). When the user names a SPECIFIC person to add ('add John Doe to the pipeline'), use filter_mode 'all': the ICP filter is meant for bulk sourcing and could reject an individually chosen contact. A 1st-degree profile with an ONGOING LinkedIn conversation is skipped (reported in the import summary): to hand a live thread to the AI, use list_manual_conversations + adopt_conversation instead. Confirm the list with the user before queuing. IMPORTANT for agencies running several clients: pass campaign_id to land the prospects in the RIGHT client's campaign (they are also evaluated against THAT campaign's ICP). Omitting it defaults to the primary campaign, so always set it when the user is working on a specific client -- call list_campaigns first if unsure which id.
Hand a manually-started LinkedIn conversation over to MimikFlow (the machine automating the user's LinkedIn prospecting): creates the contact as a lead in the campaign, imports the full message history, and from then on the machine works the thread under the campaign's settings. handled_by 'setter' (default): the AI answers replies, sends spaced reminders on silence and pushes toward the conversion goal. handled_by 'me': the thread is only tracked (visible in the inbox, replies surfaced), no AI message ever. CAUTION with 'setter': if the contact's last message is still unanswered the AI will answer it on its next run, and reminders resume on silence -- say this to the user and get an explicit confirmation per conversation before calling. Get chat_id from list_manual_conversations.
Approve a pending draft: it is sent to the prospect on LinkedIn through the normal pipeline (daily LinkedIn caps apply) and the lead's status advances accordingly. Read the conversation first with get_conversation.
Take prospects out of the active pipeline by setting their status to 'dropped': MimikFlow (the machine automating the user's LinkedIn prospecting) stops ALL automated outreach to them -- no more reminders, no AI replies -- while the lead, its conversation history and the LinkedIn connection are kept. This is the right way to 'remove' e.g. competitors or bad fits from the pipeline (hard deletion only exists in the app). Safety: if a dropped prospect writes back later, the reply is still surfaced to the user. DESTRUCTIVE-ISH: always list the exact leads (names + ids) to the user and get an explicit confirmation BEFORE calling. Any pending drafts for these leads are cancelled. Max 50 ids per call (from list_leads).
Replace a pending draft's text with an improved version, then send it. Keep the user's voice; write in the same language as the conversation.
Export a slice of leads with full fields (for pushing into a CRM, a spreadsheet, or reporting). Same filters as list_leads, higher limit. Returns the MOST RECENTLY updated leads only: when `has_more` is true, `total` matching leads exist and the user should narrow the slice with `status` or export from the app. Occasional use (a few exports a day); recurring extraction is not what this connector is for.
Global state of the user's MimikFlow account (MimikFlow = a machine that automates their LinkedIn B2B prospecting 24/7: finds prospects, sends invites, personalized DMs, follow-ups, and an AI setter that answers prospects to book meetings). Returns campaigns, LinkedIn session health, which pipelines are on/off, lead counts per status, inbox items waiting for the user (drafts to approve + escalated conversations), and the LinkedIn safety limits in force. Reading the pipeline states: the extra lead sources (engagement_scraper = reactions to the user's posts, profile_views = profile visitors, invite_manager = incoming invites, first_degree_scanner = their existing 1st-degree network) are OPT-IN and start off for everyone -- an off source is usually a setup choice to suggest enabling, EXCEPT the ones listed in `locked_sources`: those are unavailable on the user's current plan (e.g. first_degree_scanner needs a PAID Pro+ plan, it is not included in the free trial) -- never suggest enabling a locked source, present it as what unlocks when they upgrade/subscribe. tracking always runs. The pipeline ids in the payload are internal: to the user, call each step by its product name in their language (la recherche de prospects / prospect search, les demandes de connexion / connection requests, le premier message / the first message, les relances / follow-ups, l'IA qui répond aux prospects...), never by its id. Call this first to orient yourself.
Read a campaign's current settings, i.e. everything that drives how the AI finds prospects and writes to them: targeting (my_target = ideal customer in plain text, my_anti_target = who to avoid), who_am_i (who the user is), my_product (their offer), the conversion goal (goal_type 'call' = book a meeting, 'link' = drive to a URL), the booking `calendar` block (connected / provider / applies_from / auto_book), voice (communication_style, style_examples, social_proof_stories, my_objections = the user's answers to common objections), and OPTIONAL behavior overrides (custom_cold_dm_instructions / custom_follow_up_instructions / custom_setter_instructions, setter_custom_stop_condition). IMPORTANT on booking: when `calendar.connected` is true, an EMPTY goal_link is perfectly normal and NOT a misconfiguration -- the AI reads the user's real availability and books the slot itself, so no link is needed. Only report a missing booking link when the goal is 'call' AND no calendar is connected. IMPORTANT: an empty custom field is normal, NOT a gap: MimikFlow's default behavior (varied reminders, respecting a no, stopping on silence, escalating to the human) applies on its own; these fields only personalize it further. The key names are internal: to the user, speak of each field by its plain meaning in their language ('ta cible', 'ton offre', 'tes réponses aux objections'), never by its raw key. ALWAYS read this before updating anything.
Full detail of one lead: LinkedIn profile info, status, and the complete conversation thread between the user's AI and the prospect ('us' = messages sent from the user's account, 'prospect' = their replies), plus any draft waiting for approval. ALWAYS read this before approving a pending message or replying to an escalated lead. Long threads are cut to the 100 most recent messages: when `truncated` is true the thread STARTS EARLIER than what you see (`total_messages` = the real count), so never conclude anything about how the conversation began.
Read a campaign's fine-grained machine settings: reminder cadence (timing_* waits, timing_max_follow_ups, the selected offer-pitch follow-up, per-phase relance styles), first-message tone (cold_dm_formality tu/vous, style, length, emoji, CTA mode), setter tone (setter_style, setter_max_phrases), sending modes (cold_dm_mode / setter_mode: 'auto' sends by itself, 'semi_manual' queues every draft for the user's approval), sending days/hours per pipeline, daily/weekly volume caps, market/language settings, and the meeting follow-through (Suivi RDV) keys: nurture_pre_meeting / nurture_post_meeting (opt-in value messages before/after a booked meeting), meeting_reminder + meeting_noshow_recovery + meeting_cancel_recovery (live defaults, 'off' disables), and setter_post_booking (the AI answers booked prospects' simple questions, stays silent on thanks, escalates reschedules to the human). Every empty value simply means MimikFlow's sensible default applies (these are tuning knobs, not required configuration). The keys are internal vocabulary: to the user, name each setting by what it does in their language ('le délai entre deux relances', 'le tutoiement du premier message'), never by its raw key. Read before updating with update_pipeline_settings.
The user's LinkedIn prospecting KPIs and funnel for a period: connection invites sent/accepted, first messages (cold DMs) sent, prospect replies, conversion goals reached (goal_reached = a won lead, usually a booked meeting), with per-step drop rates. Use it for recaps ('how is my prospecting going?') and to diagnose where the funnel leaks. A frequent leak: invites accepted but few replies, which usually means the first message's approach (formality, style, hook) does not fit the audience -- read real threads and the campaign profile, then tune the cold_dm_* settings. window is '7d', '30d' or 'lifetime'. Report the numbers to the user in plain words in their language (invitations envoyées / acceptées, premiers messages, réponses, objectifs atteints), never as raw field names.
Raw material to coach the user on their sales conversations: full threads of recently WON leads (conversion goal reached) and LOST leads (dropped after the prospect had replied). YOU do the analysis: recurring objections, drop-off points, what worked in wins. Then translate EVERY finding into a concrete settings change (update_targeting for who gets contacted; update_campaign_profile for my_objections, the custom instructions, style or proof; update_pipeline_settings for the first-message tone when the opener does not fit the profiles contacted) and offer to apply it. Frame findings as settings to improve, never as defects of the product. outcome is 'won', 'lost' or 'both'.
The user's connected LinkedIn accounts. Most users have ONE; an AGENCE user runs several (e.g. one per client) from this single connector. Returns each account's id, name (label), LinkedIn plan, status (active/disconnected), how many campaigns run on it, and its lead-dedup pool (accounts sharing a non-empty pool never prospect the same people). Use this to know which accounts exist, then list_campaigns to see the campaigns of each, and target any campaign by its campaign_id -- one connector pilots every account.
The user's prospecting campaigns. A campaign bundles one ideal customer profile (ICP) + one offer + one tone + its own leads and conversations; most users have one, agencies run several in parallel. Returns id, name, status (active/archived), lead count, and the LinkedIn account it runs on (linkedin_account_id + account_name -- an Agence user targets a client by picking that client's campaign). Optional `account_id` filters to one account's campaigns. When a tool gets no campaign_id it uses the primary (oldest active) one.
Conversations MimikFlow's AI deliberately handed over to the human (status talk_to_human): the prospect asked something out of the AI's scope, requested a human, or a custom stop condition matched. The machine will NOT answer these; they wait for the user. Read each thread with get_conversation, then help the user craft an answer and send it via reply_to_lead. Covers every campaign by default (pass campaign_id to narrow to one client). total / has_more / next_offset describe escalation_cards; leads_waiting_total is the real number of prospects waiting for the user, of which the 30 most recent are listed.
List the user's prospects (leads found and worked by their automated LinkedIn prospecting). Filterable by status (comma-separated; 'connected' expands to every status where the LinkedIn relationship exists), tag name, or free-text search on name/position. Status meanings: new = found not yet contacted, connection_request = invite sent, connection_accepted = invite accepted, first_contact = first DM sent, discussion = the AI is talking with them, follow_up = being reminded, snoozed = re-engage at a future date, goal_reached = WON, talk_to_human = needs the user, dropped = abandoned. These codes are internal: report a status to the user in plain words in their language ('invitation envoyée', 'en discussion', 'objectif atteint'), never as the raw code. Paginated: `total` is the real number of matching prospects and `has_more` says whether you only saw a slice -- never present one page as the whole base, page with `next_offset` or narrow the filters.
LinkedIn conversations in the user's inbox that MimikFlow (the machine automating their LinkedIn prospecting 24/7) is NOT tracking: threads the user started or handled by hand, outside the automated pipeline. Scans the most recent chats and returns the untracked ones with the contact's name, headline and a chat_id. Use it when the user wants to see their manual conversations or hand one over to the machine; then call adopt_conversation with the chosen chat_id. Read-only: nothing is saved or contacted.
Meetings the AI setter booked with prospects in the user's real calendar (the usual conversion goal). Returns prospect, datetime and status. upcoming_only=false includes past meetings. CAVEAT: only meetings stamped through a CONNECTED calendar appear here; a meeting agreed in conversation or self-booked via a link often does not. goal_reached in get_pipeline_stats is the source of truth for won leads -- never conclude 'no meetings booked' from this list alone.
The user's approval inbox: messages MimikFlow's AI drafted for prospects but is holding until the user validates them (validation mode, or a coherence check flagged the draft). Nothing in this list has been sent. Workflow: read each lead's thread with get_conversation, then approve_pending_message (send as is), edit_and_approve_pending_message (improve then send), or reject_pending_message (never send). Covers every campaign by default (pass campaign_id to narrow to one client), oldest first, and paginated: `total` is the real backlog, `has_more` says a slice is missing -- page with `next_offset` before telling the user their inbox is empty or counting it.
List the user's lead tags (free labels used to segment prospects, e.g. by cohort, event or offer) with the number of leads carrying each. Tags are usable as a filter in list_leads. Complete list, never truncated.
Reject a pending draft (it will never be sent). Setter drafts move the lead to talk_to_human, cold DM drafts drop the lead, follow-up drafts restore the previous status. Also resolves escalation cards.
Send one message to a prospect AS the user, in their existing LinkedIn conversation. Meant for escalated (talk_to_human) conversations after reading the full thread with get_conversation, and for a quick courtesy message on a WON lead right after a meeting ('merci pour ce call, je t'envoie un mail') -- a goal_reached lead keeps its won status. Write in the conversation's language and the user's voice, and get the user's OK on the wording before sending: this message goes out immediately.
Give a conversation back to the AI. When MimikFlow (the machine automating the user's LinkedIn prospecting) hands a prospect over to the human -- the user answered by hand on LinkedIn, the AI escalated, or a reply landed while the AI was off -- that conversation stays manual forever: the AI stops answering and the reminders stop. This is the return path. It first syncs the real LinkedIn thread (so the messages the user typed by hand are recorded and stop being read as a new manual takeover), then puts the prospect back under the AI: it answers on its next run when the prospect spoke last, otherwise the reminder sequence resumes. The prospect's history and the notes the user wrote are kept, and the 'needs your attention' cards for that prospect are cleared. Only works on a prospect currently handled by the human. If the user answers by hand again afterwards, the conversation goes back to them, which is intended. Confirm with the user before calling: the AI will write to this prospect again.
Trigger an immediate one-off run of a MimikFlow pipeline instead of waiting for its schedule (e.g. lead_scraper to go find prospects right now, connection_sender to send today's invites). All daily LinkedIn safety limits still apply, so 'now' never means 'more'. Not available for setter (it runs whenever a prospect replies) and tracking. To the user, describe the action in product words in their language ('je relance la recherche de prospects'), never with the internal pipeline id.
Full-text search across every prospect conversation (e.g. 'pricing', 'not interested', a competitor name). Returns matching leads with the matched snippets. Scans the 200 most recent matching messages only: `truncated` true means older matches exist beyond what is shown, so present the results as examples, never as an exhaustive count.
MimikFlow's official help center content. Use it to answer ANY how-to or support question about MimikFlow (setup, features, plans, LinkedIn safety, billing, calendar, broadcasts, MCP...) with accurate product answers instead of guessing. Without arguments: the catalog of topics with their questions. With topic_id: that topic's full content. With query: every topic matching the text. Base your answer on this content and answer in the user's language.
Preview-search LinkedIn prospects matching a free-text query (e.g. 'expert comptable Bordeaux' or 'SaaS founder Paris hiring SDR'). Returns candidate profiles WITHOUT contacting or saving anything, marking those already in the campaign. Review with the user, then pass the chosen URLs to add_prospects_to_campaign.
Give the machine fresh news from the user (a new case study, a new result, a new offer detail). For the next 30 days, MimikFlow swaps ONE reminder per lead with a re-offer message built from this news, a strong way to revive silent prospects. Max 600 chars, strictly factual (the AI must never invent numbers). Empty text clears it.
Schedule a future re-engagement for a lead. Two uses: (1) the prospect asked to be re-contacted later ('come back next month') -- the lead is snoozed and MimikFlow wakes it at the date with one warm re-engagement message, then resumes its normal cadence; (2) after a meeting happened (lead already won / goal_reached) -- the lead KEEPS its won status and gets ONE follow-up at the date, with no automatic cadence after it. Pass the optional `note` to give the AI real context for that message (summary of the meeting or call, the offer made, the agreed next step): the follow-up will reference it naturally instead of shipping a generic re-engagement. callback_at is an ISO date clamped to 1-90 days from now; null cancels the schedule and clears the note.
Attach a tag (free label used to segment prospects) to a list of leads, creating the tag if it does not exist yet. Idempotent: already-tagged leads are unaffected. Useful to mark a cohort before filtering or reporting on it later.
Turn one of MimikFlow's automated pipelines on or off for a campaign. The prospecting chain: lead_scraper ('la recherche de prospects', finds new prospects that match the ICP), connection_sender ('les demandes de connexion', sends LinkedIn invites), cold_dm_sender ('le premier message', first personalized message), follow_up ('les relances', spaced reminders), setter ('l'IA qui répond aux prospects'). Extra lead sources: engagement_scraper ('les réactions à tes posts', people who like/comment the user's posts), profile_views ('les visiteurs de profil'), invite_manager ('les invitations reçues'), first_degree_scanner ('tes relations de 1er degré', existing connections). These ids are tool-call vocabulary only: to the user, always name the step by its product name in their language, never by its id. Changes apply within minutes; use run_pipeline_now for an immediate run. Warn the user before turning OFF part of the chain: leads then pile up unprocessed at that step.
Update the campaign's settings. Writable keys: who_am_i, my_product, my_objections (answers to common objections), sender_name, communication_style, style_examples, social_proof_stories, goal_type ('call' or 'link'), goal_link, goal_label, and the OPTIONAL behavior overrides custom_cold_dm_instructions / custom_follow_up_instructions / custom_setter_instructions plus setter_custom_stop_condition (extra hand-off situations). These overrides personalize MimikFlow's built-in behavior (which already varies reminders, respects a no, stops on silence); leaving them empty is a valid, normal state, so only propose filling one to address a SPECIFIC pattern seen in the user's own conversations. Read get_campaign_profile first, change only what the user validated, and APPEND to existing instructions rather than overwriting them unless the user asks. Present each change in plain words ('tes réponses aux objections'), never by raw key name.
Update the machine's fine-grained settings (same keys as get_pipeline_settings): reminder cadence and count, the selected offer-pitch follow-up, per-phase relance styles, first-message and setter tone, sending days/hours, sending modes, market/language. `target_regions` narrows prospecting to provinces / states / cities INSIDE the chosen countries (free text the user writes their own way, comma-separated, e.g. 'Quebec, Montreal' on a Canada campaign); empty means the whole countries. The first message's BASE STYLE is one choice made of two mutually exclusive keys: cold_dm_template picks a ready-made style, cold_dm_custom_template is the user's own example message the AI imitates. Setting either one automatically clears the other (they are reported in `cleared`), because an example message left behind silently overrides the chosen style. Daily and weekly VOLUME limits are readable but NOT writable here: how much a LinkedIn account may send is a human decision taken in the app, never reshaped from a chat. Each key is validated. CAUTION on modes: 'semi_manual' means NOTHING is sent until the user approves each draft in the inbox -- a forgotten semi_manual silently freezes the whole machine, so only set it on an explicit request and remind the user to process the inbox. Confirm every change with the user before saving, describing each setting by what it does in plain words, never by its raw key.
Rewrite the campaign's ideal customer profile: my_target (who the machine should find and contact) and/or my_anti_target (who it must avoid). Write in the user's language, concrete and specific (roles, sectors, company size, geography, pains). MimikFlow's prospect finder and evaluators apply the new text on their very next run, so confirm the wording with the user before saving.
How do I improve a ChatGPT Plugin's discoverability?
The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.
Where is this profile measured?
This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.