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Flux LinkedIn MCP

von fluxgraph.appVersion 1.0.0i★ –iLäuft in der Cloud
Name in der Registryapp.fluxgraph/linkedin

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

LinkedIn intelligence: post analytics and research for public profiles and company pages.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft in der Cloud
  • Transport: Streamable HTTP
  • Kategorie: Marketing & Social Media

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 2 von 3 bestanden
  • Läuft auf dem Server des Entwicklers: Was du fragst, läuft über dessen Server.
  • Kann 60 Dinge (Tools) list_profiles, preview_profile, preview_posting_insights, preview_search_posts …
  • Die Registry nennt keinen Schlüssel zum Eintragen.

Du brauchst

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:

  1. Öffne Settings → Connectors
  2. Tippe auf Add custom connector
  3. Füge die Adresse unten ein und tippe auf Add
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Add2https://…3
https://www.fluxgraph.app/mcp

Führe das in deinem Terminal aus

claude mcp add --transport http linkedin https://www.fluxgraph.app/mcp

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "linkedin": {
      "url": "https://www.fluxgraph.app/mcp"
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "linkedin": {
      "type": "http",
      "url": "https://www.fluxgraph.app/mcp"
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

ChatGPT verbindet sich nur mit Servern im Internet:

  1. Öffne ChatGPT im Web → Settings → Connectors (Apps)
  2. Tippe auf Create oder Add (bei manchen Tarifen musst du zuerst Developer mode unter Advanced einschalten)
  3. Füge die Adresse unten ein, gib ihr einen Namen und speichere
  4. Wenn eine Anmeldung verlangt wird, melde dich beim Dienst des Entwicklers an
SettingsConnectors1+ Create2https://…3
https://www.fluxgraph.app/mcp

Menünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 6. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

  • 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, average engagement, the format that beats the baseline, the top post and the recent trend, plus a preview_id. The full breakdo

  • 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 engagement trend by format. Requires a free Flux account; calling it asks the person to sign in where the client supports it, ot

  • 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 engagement. Requires a free Flux account; calling it asks the person to sign in where the client supports it, otherwise use c

  • 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 sign-in; creates a free dashboard showing the latest 50 posts, one per account. Refuses if the account already has a da

  • 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 already has a profile_id and wants to read its posts. Filter by date range, post type, minimum engagement, or text. Pass `s

  • 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 trend, top format, and posting goal status.

  • 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 breakdown (likes, comments, shares, conversation rate) for every bucket. All metrics relative to the user's own baseline. P

  • 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 with avg_engagement, vs_baseline, and a sample_post_url. Mirrors the dashboard topics chart, server-side. Pass `scope`

  • 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, shares, and conversation rate. Useful for understanding whether engagement is growing or declining. Pass `scope` (a post_

  • 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 string and wants ranked persisted-post results. Pass `scope` (a post_collections.id) to limit to a specific collection.

  • 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, person_interests, hiring_signals, ad_watch) to preview the per-page cost create_stream / run_stream_now will charge. Return

  • 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 (see get_cost_estimate for the per-type cost). own_profile streams are not created here — they come from subscription c

  • list_streams

    List all research streams for the authenticated user (external profiles, companies, topics, person interests, hiring signals, ad watches, and own_profile). Pass `type` to filter. Replaces list_profiles for the streams-first world, but list_profiles continues to work for V1-compat

  • 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_interests / company stream has surfaced on its schedule.

  • 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 billing-managed and cannot be paused here.

  • 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 be resumed here.

  • 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't lost. Auto-collection is deleted with the stream. own_profile streams cannot be deleted through this tool; the own pr

  • 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 happens asynchronously. Credits are charged for pages actually walked, not pages requested: one page is taken upfront and the

  • 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` (structured fields) and `linkedin_profiles` (so profile-brief renders) — same enrichment side-effect as the other linkedin_pro

  • 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 post library (source_type='external') and linked to a linkedin_profiles row so profile-brief can render research-only p

  • 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 post library (source_type='external') and linked to a linkedin_profiles row (profile_type='company').

  • 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 subsequent queries about who-engages-with-whom are SQL, not API calls.

  • 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 the commenter and full comment text.

  • 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 a *block of text* (a draft, a paragraph, a competitor's post) and want similar posts you've already collected. For keywo

  • 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 weighting — the same model used on the /score page. Returns a predicted engagement percentile, projected engagement range, fac

  • 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 calls OpenAI to generate 5 concrete angles. Costs 5 credits per call. Pass `profile_id` to scope to a tracked profile, `co

  • 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', 'Champions'). Free — costs 0 credits.

  • 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), type='smart' with a `config` predicate (e.g. {title_contains:'VP'}) to define a dynamic segment resolved on-demand by r

  • 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 segment's `config` predicate against the people table and returns matches. Free — costs 0 credits.

  • 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 0 credits.

  • 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 skip alerts the user has already marked read. Free — costs 0 credits.

  • 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` predicate (e.g. {format:'video',min_likes:50}) to define a dynamic collection resolved on-demand by resolve_collection. Free — c

  • 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 a 'smart' collection it adds the posts as extras alongside whatever the rule already matches (resolve_collection returns

  • 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 collections (system-managed). Free — costs 0 credits.

  • 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 collection's `config` predicate against the user's posts and returns matches. Free — costs 0 credits.

  • 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 approach to reach them. Free — costs 0 credits.

  • 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 — costs 0 credits.

  • 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 engagers, then scores every connection and produces a prioritized outreach queue. Credit cost scales with targets — bou

  • 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. Free — costs 0 credits. Note: this tool requires a `campaign_id` because it writes back to the `constellation_entries`

  • get_outreach_queue

    Return a prioritized outreach queue. Provide *exactly one* of three scopes: • `campaign_id` — full Constellation queue with composite_score, pool, recommended_action, and prior outreach_log entries (the original campaign-scoped behavior). • `segment_id` — people in a saved audien

  • 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 credits. Identify the person via *exactly one* of: `target_id` (a Constellation target — original input), `person_id` (a

  • 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 can compute acceptance / reply rates over time. Free — costs 0 credits.

  • 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 / mutual) and composite-score tier. Free — costs 0 credits.

  • 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 (manual or smart — pinning into a smart collection adds it as an extra alongside the rule's matches). Costs 1 credit per

  • 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_current=true). Pure DB read — no LinkedIn pull, no credits charged. Engagers without a known current company are bucketed as

  • 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, =2 by top+mid, =3 by full hierarchy. Engagers with no current company / no industry hierarchy bucket as `_unknown`. Pur

  • 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, 'alumni' = any past or current position (most useful for page_type='SCHOOL' companies), 'any' = both. Pure DB read — no L

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026

  • ! Vorsicht

    Entwickler passt zum Repo

    Die Registry nennt kein Quell-Repo, deshalb können wir den Herausgeber (fluxgraph.app) nicht dem Code zuordnen

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • ✓ Bestanden

    Endpunkt antwortet

    Antwort in 378 ms (HTTP 200)

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Keine Anmeldung nötig

  • ✓ Bestanden

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Wir haben 60 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Im Vergleich mit anderen in Marketing & Social Mediai

  • Mehr Sterne als 0 % der anderen 2958 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 87 % der anderen 2958 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 48 % der anderen 2958 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Flux LinkedIn MCP sicher?

Er hat 2 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.0) kam vor 4 Tagen in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.

Was kann ich stattdessen nutzen?

In derselben Kategorie: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Google Analytics MCP

von surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

Läuft auf deinem Computer★ 244MITAktualisiert vor 9 Tagen
Installieren

README vom Entwickler

Keine README im Repo gefunden

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