Claude, let's write a LinkedIn post.

Return posts with full metrics and text content for a tracked profile. Supports filtering by date range, post type, minimum engagement, and text search. Pass scope to restrict to a collection. Paginated.

KPI summary for a tracked profile: total posts, avg engagement (likes/comments/shares/conversation rate), posts per week, engagement trend, top format, and posting goal status.

Optimal posting patterns for a profile: best day of week, best hour, format performance breakdown, character-length sweet spot. All metrics relative to the user's own baseline. Pass scope to recompute against a collection.

Engagement time series with gap-filled buckets, rolling averages, and trend direction. Each bucket includes avg engagement, likes, comments, shares, and conversation rate.

Search posts by keyword and/or semantic similarity. Full-text search with stemming for keyword matches, pgvector embeddings for semantic matches. Results ranked by relevance.

Find posts semantically similar to input text using OpenAI embeddings and pgvector cosine similarity. Scope to a profile or a collection. Returns posts sorted by similarity with engagement metrics.

Predict how a draft post will perform against the user's historical data. OLS regression with detrending, ridge regularization, and recency weighting — same model as the /score page. Returns predicted engagement percentile, projected range, factor breakdown, similar past posts, and improvement suggestions.

Given a topic, suggest distinct content angles informed by what performs well in the user's scoped data. Pulls top historical posts as context and asks OpenAI to generate 5 concrete angles.

List all tracked LinkedIn profiles for the authenticated user. Returns profile IDs needed by other tools.

List all research streams (external profiles, companies, topics, person interests, hiring signals, ad watches, own_profile). Pass type to filter.

Create a new research stream. Running it on schedule costs credits — see get_cost_estimate for per-type cost. own_profile streams come from subscription checkout, not this tool.

Return the most recent posts a stream has collected into the library, newest first by published_at.

Pause a stream so it stops running on its cron schedule. Existing posts remain in the library.

Resume a paused stream. Queues it to run on the next cron tick.

Delete a stream and its runs. Posts it collected stay in your library so historical data isn't lost. own_profile streams can't be deleted here — cancel the subscription instead.

List all post collections for the authenticated user, with member counts.

Create a new post collection. Manual or smart (predicate-based).

Add one or more posts (by post_id) to a collection. Existing members are silently ignored.

Remove one or more posts (by post_id) from a collection. Missing members are silently ignored.

Resolve a post collection into a concrete list of post_ids. Works for both manual and smart collections.

List all audience segments for the authenticated user, with member counts. Segments are named groups of people (e.g. ‘ICP — VPs of Marketing’, ‘Champions’).

Create a new audience segment. Manual or smart (template-based).

Add one or more people (by person_id) to an audience segment.

Remove one or more people (by person_id) from an audience segment.

Resolve an audience segment into a concrete list of person_ids.

List available smart-segment templates. Pass a template id to create_segment to spin up a preconfigured segment.

Save a LinkedIn post to your library by URL. Resolves the post via HarvestAPI and stores it with source_type='saved'. Optionally adds the post to a manual collection. Failed lookups don't charge.

Return recent alerts for the authenticated user's streams.

Fetch recent posts from a LinkedIn person profile. Results also stored in the post library (source_type='external') and linked to a linkedin_profiles row.

Fetch recent posts from a LinkedIn company page.

Search LinkedIn posts by keyword. Returns a single page of matching posts.

Fetch the recent posts a LinkedIn person has reacted to. Useful for inferring interests.

Fetch the recent posts a LinkedIn person has commented on. Useful for inferring interests and conversation partners.

Fetch the people who reacted to a single LinkedIn post (with reaction kind). Engagers are persisted to the post_engagements graph.

Fetch the people who commented on a single LinkedIn post (with comment text). Each comment is persisted to post_engagements.

Search LinkedIn people by company, title, location, or keywords. Returns a single page of profiles.

Search LinkedIn companies by keywords, industry, or location. Returns a single page of companies.

Search LinkedIn job postings. Useful for tracking hiring signals at target companies.

Search the LinkedIn ad library. Useful for tracking competitor ad creative and messaging.

Create a Constellation outreach campaign. Groups target accounts, people you care about at those accounts, and warm connections you could approach.

Add one or more target companies to a campaign. map_constellation is then run per-account.

Map the professional graph around a target company. Finds senior decision-makers, pulls each target's recent posts/reactions/comments to identify engagers, scores every connection, and produces a prioritized outreach queue. Scales with max_targets; actual cost is reported in the response.

Re-score all constellation entries in a campaign and rewrite queue positions from highest to lowest composite score. Run after new engagers or targets are added.

Return the prioritized outreach queue for a campaign, sorted by composite score. Each entry includes person details, pool (coworker/engager/mutual), recommended action, and prior log entries.

For a Constellation target, return the handful of their recent posts that most closely overlap with the topics you post about yourself — plus suggested talking points. Use before a warm comment or DM.

Append an entry to the outreach log: connection requests, acceptances, replies, or no-responses. Feeds get_campaign_stats.

Summary stats for a campaign: target count, entry count, outreach volume, and acceptance / reply rates broken down by pool and score tier.

Return the authenticated user's current credit balance, this period's monthly allocation, and credits used since the period started.

Given an MCP tool name, return its credit cost so you can preview an action before running it. Returns { tool_name, cost, balance, sufficient }.

Recent credit_ledger transactions for the authenticated user. Filter by tool, reason, or date range. Paginated.