Flux LinkedIn MCP

• list_profiles — List all tracked LinkedIn profiles for the authenticated user. Returns profile IDs needed by other tools.
• preview_profile — Analyze a public LinkedIn profile or company page without a Flux account: pulls the latest ~50 posts (once per profile) and returns a teaser: post count, averag
• preview_posting_insights — Full breakdown for a previewed profile (from preview_profile): best day, hour, format and length, the top and bottom 5 posts with measured reasons, and engageme
• preview_search_posts — Keyword search over the latest 50 posts of a previewed profile (from preview_profile). Case-insensitive substring match; returns matching posts ordered by engag
• claim_preview — Make a profile from preview_profile your own Flux dashboard. Call this only when the person says the profile is theirs: the person cannot undo a claim. Requires
• get_posts — List a tracked profile's persisted posts with full metrics and text — query against the local post library, no LinkedIn pull, free. Use this when the caller alr
• get_profile_summary — Get KPI summary for a tracked profile: total posts, average engagement (broken down by likes/comments/shares/conversation rate), posts per week, engagement tren
• get_posting_insights — Get optimal posting patterns for a profile: best day of week, best hour, format performance breakdown, and character length sweet spot. Includes full metric bre
• get_topic_insights — Surface the most-frequent topics in a profile's posts, with engagement context. Returns top N unigrams and (optionally) top N bigrams ranked by post count, each
• get_engagement_trends — Get engagement time series for a profile with gap-filled buckets, rolling averages, and trend direction. Each bucket includes avg engagement, likes, comments, s
• search_posts — Keyword + semantic search over persisted posts in the local library — full-text + pgvector cosine, no LinkedIn pull, free. Use this when the caller has a query
• get_credit_balance — Return the authenticated user's current credit balance, this period's monthly allocation, and credits used since the period started. Free.
• get_usage_history — Return recent credit_ledger transactions for the authenticated user. Filter by tool name, reason, or date range. Paginated. Free.
• get_cost_estimate — Given an MCP tool name, return its credit cost so you can preview an action before running it. Also accepts a stream type (external_profile, company, topic, per
• create_stream — Create a new research stream (external profile, company, topic, person interests, hiring signals, or ad watch). Running the stream on its schedule costs credits
• list_streams — List all research streams for the authenticated user (external profiles, companies, topics, person interests, hiring signals, ad watches, and own_profile). Pass
• get_stream_feed — Return the most recent posts a stream has collected into the library, newest first by published_at. Use this to browse what a topic / external profile / person_
• pause_stream — Pause a stream so it stops running on its cron schedule. Existing posts remain in the library. Use resume_stream to re-enable it. own_profile streams are billin
• resume_stream — Resume a paused stream. Sets active=true and queues it to run on the next cron tick by clearing next_run_at. own_profile streams are billing-managed and cannot
• delete_stream — Delete a stream and its stream_runs. Posts collected by the stream stay in your library (stream_id is set to NULL via ON DELETE SET NULL) so historical data isn
• run_stream_now — Trigger an immediate run of an active stream, bypassing its schedule. The run is fire-and-forget — the response confirms the dispatch but post collection happen
• linkedin_profile_info — Fetch a LinkedIn person profile (headline, current role, work history, education, location). Costs 5 credits per call. Results are upserted into `people` (struc
• linkedin_profile_posts — Fetch recent posts from a LinkedIn person profile. 5 credits per page of 50, up to 250 posts, charged only for pages actually fetched. Results are stored in the
• linkedin_company_posts — Fetch recent posts from a LinkedIn company page. 5 credits per page of 50, up to 250 posts, charged only for pages actually fetched. Results are stored in the p
• linkedin_post_search — Search LinkedIn posts by keyword. Costs 5 credits per call. Returns a single page of matching posts.
• linkedin_profile_reactions — Fetch the recent posts a LinkedIn person has reacted to. Useful for inferring interests. Costs 5 credits per call.
• linkedin_profile_comments — Fetch the recent posts a LinkedIn person has commented on. Useful for inferring interests and conversation partners. Costs 5 credits per call.
• linkedin_job_search — Search LinkedIn job postings. Useful for tracking hiring signals at target companies. Costs 5 credits per call.
• linkedin_ad_search — Search the LinkedIn ad library. Useful for tracking competitor ad creative and messaging. Costs 10 credits per call.
• linkedin_people_search — Search LinkedIn people. Filter by company, title, location, or free-text keywords. Costs 5 credits per call. Returns a single page of matching profiles.
• linkedin_company_search — Search LinkedIn companies. Filter by keywords, industryId, or location. Costs 5 credits per call. Returns a single page of matching companies.
• linkedin_post_reactions — Fetch the people who reacted to a single LinkedIn post. Costs 5 credits per call. Engagers (with reaction kind) are persisted to the post_engagements graph so s
• linkedin_post_comments — Fetch the people who commented on a single LinkedIn post (and their comment text). Costs 5 credits per call. Each comment is persisted to post_engagements with
• find_similar_posts — Find persisted posts whose embeddings are nearest to a free-text query — pgvector cosine over the local post library, no LinkedIn pull, free. Use when you have
• score_draft — Predict how a draft post will perform against the user's historical data. Uses an OLS regression model with detrending, ridge regularization, and recency weight
• suggest_angles — Given a topic, suggest distinct content angles informed by what performs well in the user's scoped data. Pulls top-performing historical posts as context and ca
• list_segments — List all audience segments for the authenticated user, with member counts. Audience segments are named groups of people (e.g. 'ICP — VPs of Marketing', 'Champio
• create_segment — Create a new audience segment (named group of people) for the authenticated user. Set type='manual' for a hand-curated list (use add_to_segment to populate it),
• add_to_segment — Add one or more people (by person_id) to an audience segment. Existing members are silently ignored. Free — costs 0 credits.
• remove_from_segment — Remove one or more people (by person_id) from an audience segment. Missing members are silently ignored. Free — costs 0 credits.
• resolve_segment — Resolve an audience segment into a concrete list of person_ids. For manual / auto_stream segments, returns stored members. For smart segments, evaluates the seg
• list_segment_templates — List available smart-segment templates. Pass a template id to create_segment to pre-fill its `config` predicate without crafting one from scratch. Free — costs
• get_alerts — Return recent alerts for the authenticated user's streams. An alert is emitted whenever a scheduled stream run surfaces new items. Pass `unread_only=true` to sk
• create_collection — Create a new post collection for the authenticated user. Set type='manual' to hand-curate posts with add_to_collection, or type='smart' with a `config` predicat
• add_to_collection — Pin one or more posts (by post_id) into a collection you own — works on any collection type. On a 'manual' collection this is the only membership mechanism; on
• remove_from_collection — Remove one or more posts (by post_id) from a collection. Missing members are silently ignored. Free — costs 0 credits.
• list_collections — List all post collections for the authenticated user, with member counts. Includes manual collections, smart collections (predicate-based), and auto_stream coll
• resolve_collection — Resolve a post collection into a concrete list of post_ids. For manual / auto_stream collections, returns stored members. For smart collections, evaluates the c
• create_campaign — Create a Constellation outreach campaign. A campaign groups target accounts, the people you care about at those accounts, and the warm connections you could app
• add_campaign_accounts — Add one or more target companies to a Constellation campaign. Each account is a company you want to reach; map_constellation is then run per-account. Free — cos
• map_constellation — Map the professional graph around a target company. Finds senior decision-makers at the account, pulls each target's recent posts/reactions/comments to identify
• score_connections — Re-score all constellation entries in a campaign and rewrite queue positions from highest to lowest composite score. Use after new engagers or targets are added
• get_outreach_queue — Return a prioritized outreach queue. Provide *exactly one* of three scopes: • `campaign_id` — full Constellation queue with composite_score, pool, recommended_a
• get_engagement_brief — For one person, return their recent posts most relevant to what you post about — plus suggested talking points. Use before a warm comment or DM. Free — costs 0
• log_outcome — Append an entry to the outreach log for a Constellation campaign. Use to record connection requests, acceptances, replies, or no-responses so get_campaign_stats
• get_campaign_stats — Summary stats for a Constellation campaign: target count, entry count, outreach volume, and acceptance / reply rates broken down by pool (coworker / engager / m
• save_post — Save a LinkedIn post to your library by its URL. Resolves the post and stores it with source_type='saved'. Optionally pins the post into any collection you own
• get_post_engagers_by_company — Given a LinkedIn post URL or id, return the companies whose people engaged (reacted/commented), ranked by engager count. Joins through person_positions(is_curre
• get_engagement_industry_breakdown — Histogram of engagers' companies grouped by industry. Pivots on companies.industry_hierarchy (e.g. 'Tech > Software Development'). Depth=1 buckets by top-level,
• get_alumni_engagers — Given a company URL or id, return engagers (across your collected posts) who have a position at that company. Relation filter: 'coworker' = current employees, '
• get_engager_position_history — Return a person's full employment timeline from the position graph. Person must have engaged on at least one of your collected posts (engagement gate). Sorted c
• get_target_warmth_brief — For a target person, summarize all engagement evidence between them and your collected posts: posts they reacted to, posts they commented on, frequency, recency
• traverse_graph_help — Returns the schema, FK edges, and 5 canonical SQL examples needed to write your own SELECT against the engagement graph via traverse_graph. Also returns YOUR re
• traverse_graph — Executes a TS-validated SELECT-only SQL query against the engagement graph and returns rows. CALL traverse_graph_help FIRST to get schema + caller_user_ids + ca
• get_company_engagement_overlap — Given two companies, return engagers across your collected posts who engaged with BOTH companies' posts. Cross-account intelligence — finds people interested in
• get_outreach_path — Given a target person, find the shortest warm-intro path through your engager network. Walks coworker (shared current company) + alumni (shared past company / s
• get_post_set_engagers — Return the consolidated, deduped people who reacted to or commented on a SET of posts — one tracked profile's posts (profile_id) or a post collection (collectio

No hidden text found in the tool definitions.

Text a person reading a tool definition does not see and a model does. Invisible characters can be pasted in by accident; this says what is there, not why. Covers tools only, not prompts or resources.