"A tool for identifying relevant LinkedIn connections based on expertise" matching MCP tools:

• bulk_schedule

  SendIt

  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

  Connector

• register_derived_asset

  VarynForge

  Register a derived asset (LinkedIn carousel PDF, social post, video, image) produced from an article suggestion. Appends a distribution-ledger row so the suggestion shows everything it produced — the article plus its derivatives — for content-ROI reporting (get_article_suggestion returns them as derivedAssets). Pass `channel` (reels | youtube | x | linkedin) so the app can show per-channel distribution status; register again with a new URL for repeat posts on the same channel — every registration is kept. `scheduledFor` records a future post date from an external scheduler (Buffer etc.) for display only — VarynForge never posts on your behalf. Derivative rows never affect publish status or Search Console attribution; use mark_article_published for the article itself.

  Connector

• search_google_xray

  LinkedIn MCP Server (Salesbot)

  Google X-Ray search for public LinkedIn profiles via Google operators (site:linkedin.com/in). Useful when you don't want to consume LinkedIn search limits, and it CAN target a specific person (put the name/company in `keywords`). Found profiles are saved into your contacts (in a 'Google X-Ray' list, deduplicated by profile URL). Returns JSON `{ found, saved, rejected_low_quality, contacts, … }` where each item in `contacts` has `contact_id`, `full_name`, `profile_url` (note: this tool returns `contacts`/`profile_url`, unlike search_linkedin_people which returns `results`/`linkedin_url`). Saved leads are UNVERIFIED cached snippets — run enrich_contacts before trusting the current company. To move them into the CRM, add them to a campaign with add_contacts_to_campaign (auto-creates CRM leads) or use a CRM tool like set_deal_stage.

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• save_lead_message

  LinkedIn MCP Server (Salesbot)

  Store a generated outreach message on a CRM lead so it becomes durable context — e.g. an email, an email follow-up, a LinkedIn message or LI follow-up. The CRM is a 'sponge': you save the copy here, then read it back later (get_lead_context / list_lead_messages) and push it to the right channel via that channel's own tool/MCP (e.g. Smartlead for email). Does NOT send anything. Pass message_id to update an existing draft instead of creating a new one.

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• scenario.get

  Cloud World Model

  Hydrate one built-in scenario from the live Cloud World Model scenario library. Prerequisite: a scenario id returned by scenario.list. Returns the complete selected scenario graph, including resources and connections plus optional seed, resilienceConfig, protectedResilienceConfig, traffic/failure presets, and real-world incident metadata. The response includes both title and name for compatibility; pass resources and connections, and optionally seed/resilienceConfig, to simulation.create when you need to edit or inspect the graph. For the shorter handoff, pass the id as scenarioId instead. The likely next tool is simulation.create.

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• list_platforms

  BulkPublish

  List every social platform BulkPublish supports and whether it is currently available. Check this before telling a user they can connect a platform or scheduling a post to one: a platform in state 'off' rejects post creation with a 403 PLATFORM_DISABLED error and holds any already-scheduled posts until it is re-enabled, and one in state 'connect_off' cannot accept new connections although existing channels keep publishing. Disabled platforms are still listed, with enabled=false and a reason. A platform may also carry a 'variants' object keyed by channel accountType for sub-platforms gated on their own: LinkedIn reports variants.organization for company pages (a separate LinkedIn app with its own review), while the platform-level state covers personal profiles — so pages can be paused while personal-profile posting is live. A variant is never more permissive than its parent, and when a variant blocks a write the 403 PLATFORM_DISABLED error carries an accountType field naming it. Use this when the user asks which platforms are supported or available, or a connect/publish attempt failed with PLATFORM_DISABLED.

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• get_expertise_badge

  Almured

  Fetch a portable, HMAC-signed expertise badge for an agent (yourself or another). WHEN TO USE - Before relying on a response from an unfamiliar agent, to check their per-category expertise tier and total ratings. - To display your own credibility to a user or third-party verifier. - To produce a verifiable badge envelope you can paste into off-platform contexts (signed payload + verify_url). WHEN NOT TO USE - For real-time consultation activity — use browse_consultations. - For raw rating history — the badge exposes aggregates, not individual ratings. BEHAVIOR - Read-only. Rate-limited to 60 req/min per agent. - agent_id is optional. If empty, returns the calling agent's own badge (auth required for self-lookup). If provided, returns the public badge for that agent (no auth required). - Returns: display_name, agent_id, member_since, posted/responded counts, per-category expertise tiers (level, useful_count/total_rated), HMAC-SHA256 signature over the canonical JSON payload, and a verify_url. - Third parties can POST {badge, signature} to the verify_url to confirm the payload was issued by Almured and not tampered with. - Returns a not-found error if agent_id does not resolve to an active agent. WORKFLOW - Pair with rate_response: ratings on your responses feed expertise tiers visible in this badge. - The signed envelope is the canonical way to surface Almured credibility outside this MCP server.

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• c2b_append

  Versium REACH

  Get business demographic details for consumers. Identify the consumer with a LinkedIn URL, or with first name, last name, and one of: email, phone, or city and state. Retrieve job title, seniority, department, business email, LinkedIn profile, and complete business information. Use this tool when users ask for 'C2B', 'c2b', or 'Consumer to Business Person' data **Tips for Best Results:** - Provide full name and consumer email for best match quality - LinkedIn URLs must be in format: linkedin.com/in/username - Use `rcfg_require_email` to return only records with business email - Use `rcfg_require_value` to filter by job title, department, or other attributes

  Connector

• zeekeo_create_campaign

  rankparse-mcp

  Creates a Zeekeo LinkedIn campaign: sends a connection invite using invite_template_id, and optionally — if followup_template_id is given — waits for the invite to be accepted, then sends a follow-up message using that template. Create templates first with zeekeo_create_template. Provide exactly one of filter_url (a LinkedIn search results URL) or profile_urls (specific profiles) as the target. This starts REAL LinkedIn automation once the campaign has profiles in it — confirm with the user before calling. Requires the user to have connected their own Zeekeo Launchpad account. Direct them to rankparse.com/dashboard/integrations to connect it.

  Connector

• brain_get_thought_graph_paginated

  personalbrain-mcp

  Cursor-based paginated traversal of a thought's connections. Requires npub for credit billing. ⚠️ NOT AUTHORITATIVE FOR RECENT CHANGES. Same cached graph layer as get_thought_graph (upstream: TheBrainTech/thebrain-api-quickstart-python#2) — lags writes by hours-to-days and does not reflect updates or deletes. Use for traversal/ID discovery, never as read-after-write verification; confirm mutations by ID with get_thought.

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• list_expert_profiles

  Taste

  Returns currently-available expert taglines (pseudonymous descriptions of the kinds of expertise on hand) plus the real-time count of online expert seats and estimated wait. Use this as a cheap pre-flight check before calling a paid tool. Taglines describe expertise kinds, not individuals: no per-expert PII is exposed. Free.

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• analyze_eeat

  mcp

  Analyze a website URL for E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Evaluates content quality signals based on Google's Search Quality Rater Guidelines and "Creating helpful content" documentation. Detects EEAT signals including: - Experience: First-person language, case studies, testimonials, years of experience - Expertise: Author credentials, certifications, professional memberships, topic depth - Authoritativeness: Organization schema, awards, trust badges, media mentions - Trustworthiness: HTTPS, contact info, privacy policy, source citations Also detects YMYL (Your Money or Your Life) content for health, financial, and legal topics. Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: EEAT analysis result with: - url: The analyzed URL - score: Overall EEAT score (0-100) - grade: Letter grade (A-F) - scores: Individual category scores (experience, expertise, authoritativeness, trustworthiness) - issues: Categorized issues (critical, warnings, info) - signals: Detected EEAT signals - meta: Extracted meta information - recommendations: Prioritized list of improvements - cached: Whether result was from cache

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• vest_submit_tool_request

  vest-mcp

  Submit a request to add a new AI tool to the Vest catalog. Use when the user mentions a tool they'd like to earn cashback on that isn't currently available in Vest's catalog. Collects the tool name, optional URL, use case, and contact email for follow-up. Do NOT use this when the tool is already in Vest's catalog — use vest_search_tools first to confirm. Always confirm with the user before submitting; never auto-submit based on inference.

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• mesh_publish

  MeshMarket

  List YOUR OWN tool on the exchange and earn MESH every time another agent rents it. One call: name + price, plus EITHER craft (your expertise as instructions — the house model runs it, no code or endpoint needed, min 2 MESH) OR an https endpoint the mesh proxies to. The craft stays private; buyers rent the tool, never the recipe. Your followers are notified the moment it lists. Requires your agent key as Bearer (mesh_signup mints one).

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• get_post_analytics

  ContentIn — LinkedIn Ghostwriter

  Get LinkedIn performance for one published ContentIn post: impressions, members reached, likes, comments, shares, and a derived engagement rate. IMPORTANT: metrics are fetched on a schedule and only for posts published through a connected LinkedIn account, so a post can legitimately have no numbers yet. When that happens this returns measured: false — report that honestly as 'not measured yet'. Do NOT describe an unmeasured post as having zero impressions or zero engagement; those are different claims and only one of them is true.

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• web_login

  local-mcp

  Opens a real browser window on the Mac for the user to sign into a website themselves (you never handle their password). After they log in, the session is saved on this Mac and reused by web_navigate/web_read/web_screenshot — they won't need to log in again. Use a stable `session` name per site (e.g. 'linkedin'). NOTE: automating sites like Instagram/LinkedIn may violate their terms — the user accepts that risk.

  Connector

• publish_linkedin_post

  LinkedIn MCP Server (Salesbot)

  Create a LinkedIn post on behalf of a connected profile. By default the post is saved as a 'draft' in the LinkedIn Posts page so the user can review/edit it before publishing. Set auto_publish=true to publish immediately — that path still respects the user's MCP human-in-the-loop setting (when approval is required, the post stays as a draft and the user must publish it from the LinkedIn Posts page in the app). A random 30–180 s anti-detection delay is applied before the publish call. Attachments are not supported via MCP — add images in the in-app post editor.

  Connector

• startNativeOAuth

  Duvo MCP

  Start an OAuth-based connection with a native provider (Gmail, Google Sheets, Outlook, etc.). Returns an authorization URL that must be opened in a browser by a human end-user; once they grant consent, Duvo creates the matching connection and redirects the browser to the optional `return_url` (or the Duvo dashboard if none is provided). Poll `/v2/teams/:team_id/connections` to detect the new connection.

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• cross_db_query

  ThinAir Data

  ⚠️ SQL MUST BE VALID IN EVERY DIALECT YOU TARGET — stick to ANSI-ish SELECT syntax when mixing pg/mysql/mssql. `SELECT TOP 10` (mssql) or `LIMIT` (others) will fail on the wrong side. Run the same query across 2-4 connections in parallel; returns per-connection rows + errors for diffing. Canonical use cases: regional compare (`['mssql-reporting-us', 'mssql-reporting-eu']`), cross-dialect sync check (`['prod-postgres-fleet', 'prod-mysql-app']`), 3-env drift, 4-region compare. Resolve every connection name via `list_connections` first; tool fails per-connection on unknown names. ARCHITECT-tier cap: 4 connections; https://www.thinair.co/ for unlimited. [ARCHITECT tier]

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• brain_brain_query

  personalbrain-mcp

  Primary tool for pattern-based operations on TheBrain. Requires npub for credit billing. Accepts BrainQuery (BQL) -- a Cypher subset supporting MATCH, WHERE, CREATE, SET, MERGE, DELETE, and RETURN. ⚠️ Name-based matching (MATCH by name, WHERE CONTAINS/STARTS WITH/=~) resolves through the vendor's search/name index, which is incomplete on large brains (TheBrainTech/thebrain-api-quickstart-python#1): a query may fail to match a thought that provably exists. An empty match set is NOT proof of absence — do not CREATE/MERGE a node on the assumption it is missing without an ID-based check (get_thought). Matching by ID is reliable; matching by name inherits the index's blind spots.

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