"FIRST" matching MCP connectors:
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Privacy-first, cookieless web analytics: traffic, sources, pages, goals, funnels and site setup.
SocialFaktory (https://www.socialfaktory.com) is a social media MCP server that lets your AI agent run a brand's social content with you. It reads the brands, channels and media you already have, writes posts in the brand's own voice, prices and generates short video, takes a file you upload, composes one post per channel, schedules or sends it on TikTok, Instagram, YouTube, X, LinkedIn, Facebook and Pinterest, and reads the metrics back. It is a hosted remote server at https://www.socialfaktory.com/mcp (Streamable HTTP) with OAuth 2.1 sign-in and 20 tools. Install steps cover Claude Code, Claude Desktop, Cursor, VS Code, Codex CLI, Gemini CLI and Windsurf. You stay in control. Generating spends the credits in your wallet, and the agent is told to quote the price and ask you first. Posts are drafts until you send them, and nothing reaches a channel without the publish permission you grant on the consent screen, where you also pin the connection to one brand, cap monthly spend and choose when it expires. Generating and publishing need an active SocialFaktory plan. Not available through an agent yet: cloning a video from a link, and generating still images or carousels. Connecting a social channel is a browser sign-in and stays in the app. Docs: https://www.socialfaktory.com/docs/mcp
Your agent needs public Instagram data — a creator's posts and reels, what a hashtag is producing, what a video actually says. The official Graph API only sees accounts you already own, and needs app review to see those. **What you can ask for** • "Pull this creator's last 50 posts and reels with engagement counts." • "What is trending under #skincare this week, and which profiles keep appearing?" • "Transcribe this reel and tell me what the hook in the first three seconds is." • "Read the comments on this post and group the objections." • "Which reels use this song right now?" **How to use it** Point any MCP client at https://mcp.aisa.one/instagram/mcp and sign in with OAuth — there is no key to create or paste. 17 read tools: profiles (basic and full), a user's posts, reels and highlights, post and profile digests, post comments, reels search, trending reels, reels by song, hashtag and profile search, and media transcripts. **Why this rather than the source** Public profiles without owning the account, and no app review to sit through. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Size a creator's audience here, then ask the same agent what their brand's site traffic looks like or who to contact there — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/social/mcp for X plus Instagram, Reddit, Pinterest and YouTube; https://mcp.aisa.one/gtm/mcp for those plus Similarweb and Apollo.
Privacy-first web analytics for AI agents: visitors, revenue, funnels, visitor profiles.
Cloud Blender for AI agents: build, inspect, render and animate 3D scenes over remote MCP. Keep editable .blend files and export GLB or STL. Make your first 3D asset free: 30 compute minutes/month, no credit card.
AI underwriting agents for venture capital, lending, and reinsurance — launching first for VCs. Pre-check pitch decks against your investment rubric, extract structured financial data, run quantitative analysis, screen entities, discover risks, and generate professional IC memos from a shared deal workspace. Built for ChatGPT and Claude via MCP. Every paid transaction is authorized and settled through delegare.dev
# **RChilli MCP Hub** RChilli MCP Hub is a production-grade MCP server that exposes RChilli's full HR data intelligence platform as 17 AI-callable tools across 4 categories. Built on 15+ years of HR data intelligence, it is trusted by ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. Every tool is read-only and returns a consistent, structured JSON response — no raw exceptions, no inconsistent formats. <br> --- <br> # **Tools — 17 Total** userkey and subuserid are injected automatically from your Bearer token — you never need to pass them manually. <br> --- <br> # **🔍 Resume & Job Description Parsing — 3 tools** <br> > ### **`extract_resume_data`** > > Extracts and converts resumes, CVs, and candidate documents into structured, searchable profiles with contact details, skills, experience, education, certifications, and taxonomy-enriched data for ATS, HCM, and AI recruiting workflows. When used on a careers page or application form, the same extraction call auto-fills every application field in under 10 seconds — documented to increase candidate conversion by up to 194%. Supports 40+ languages with English-normalized output for global intake, and runs in batch mode to process legacy databases or migration backlogs overnight at scale. Also supports resume reprocessing — re-running previously extracted resumes through the latest extraction logic and taxonomy version to bring older records up to current data quality, without requiring a new document from the candidate. Distinct from bulk import (first-time extraction of a new batch) and from talent data refresh (re-enrichment from a newer submitted resume). <br> > ### **`extract_resume_data_from_url`** > > Accepts a direct URL to a PDF, DOCX, or RTF file and returns the same normalized JSON profile as the Resume Data Extraction tool. Ideal for pipeline automation where resumes are stored in cloud storage, S3, or email attachments. Also supports the same auto-fill, multilingual, and batch-processing capabilities as the core extraction tool for URL-based intake sources. <br> > ### **`extract_job_data`** > > Extracts and converts job descriptions into structured hiring data including job title, required skills, preferred skills, responsibilities, experience, education, and taxonomy-normalized role requirements for recruitment automation and candidate matching. <br> --- <br> # **🧠 Skills & Job Taxonomy — 4 tools** <br> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, all aliases, related skills, proficiency levels, and O*NET/ESCO mappings. Use when you need the complete record rather than a ranked search. <br> > ### **`lookup_job_profile`** > > Returns authoritative detail for a known job profile including canonical title, SOC/O*NET code, job family, typical required and preferred skills, salary bands, and work context. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string (min 2 chars) and returns up to 10 ranked autocomplete suggestions with canonical names and categories. Prevents free-text entry errors and keeps skill data clean at point of entry. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title string and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to taxonomy profiles from the moment a recruiter starts typing. <br> --- <br> # **🛡️ Redaction, Documents & Utilities — 7 tools** <br> > ### **`redact_resume`** > > Redacts personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. Configurable redaction scope. Idempotent. <br> > ### **`reformat_resume_with_template`** > > RChilli's Resume Reformatting tool accepts any structured candidate profile and applies one of six branded templates (TM001–TM006) to produce a consistently formatted output document in PDF, DOCX, RTF, or HTML — ensuring every candidate is presented in a standardized, professional layout regardless of how their original resume was structured. Designed for staffing firms, recruitment agencies, and enterprise HR teams who need to control candidate presentation at scale, it eliminates manual reformatting effort and enforces brand consistency across all submissions. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Preserves formatting fidelity. Useful as a pre-processing step before data extraction on non-standard file types. <br> > ### **`tag_entities`** > > RChilli's Named Entity Recognition tool takes already-extracted HR text and annotates it by wrapping each recognized entity in a structured XML-style label inline — returning output such as `<job_title>Senior Data Engineer</job_title>`, `<skill>Python</skill>`, `<city>Austin</city>`, `<degree>Bachelor of Science</degree>`, and `<organization>Google</organization>` — covering 10+ HR-specific entity types including person name, state, country, date, and year. Unlike data extraction tools that produce separate field lists, tag_entities preserves the full original text structure with entities labeled in place, making the output immediately consumable by ATS field-mapping pipelines, candidate profile builders, and content annotation workflows without any offset calculation or post-processing. <br> > ### **`extract_contacts`** > > Identifies and structures names, emails, phone numbers, LinkedIn URLs, and addresses with field-level confidence scores from candidate records, emails, or documents. Safe for GDPR/CCPA workflows. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Enables radius-based candidate and job search and supports workforce planning analytics. <br> > ### **`classify_job_zone`** > > RChilli's Job Zone Classification tool reads the job profile from a resume or job description and returns its O/*NET Job Zone — one of five standardized levels ranging from Zone 1 (little or no preparation required) through Zone 2 (some preparation), Zone 3 (medium preparation), Zone 4 (considerable preparation), to Zone 5 (extensive preparation required) — based on the education, experience, and training criteria defined by O/*NET. The returned Job Zone level enables downstream workflows such as candidate-to-role fit filtering, compensation benchmarking, over/under-qualification flagging, and job architecture standardization without any manual O/*NET lookup. <br> --- <br> # **🎯 Search & Matching — 3 tools** <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one Job Description (no index required) and returns an overall match score, dimension scores, skill gap list, and natural-language explanation. Bias-controlled and audit-ready. <br> > ### **`find_matches_in_index`** > > Accepts a resume or Job Description as input and returns the top-N most similar documents from the indexed corpus ranked by semantic similarity. No index setup required for the input document. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant's pre-populated index. Supports Boolean and semantic search modes. Requires documents to be indexed before use.
Analytics for MCP servers. Query your tool calls, first-call success, retries and schema cost.
- Gigi AIOAuthai.usegigi
LinkedIn outreach from Claude with a human veto. Gigi researches each prospect and drafts the connection request and follow-ups; from Claude you review, edit and approve drafts, triage replies, create and manage campaigns, and read outreach reports. Nothing is sent without an approval, every write tool asks first, and the connector cannot bypass LinkedIn caps or sending windows. Sign-in: OAuth with your Gigi account. Setup: https://usegigi.ai/connect-claude?ref=glama
- LoomalyOAuthcom.loomaly
SEO audit of every page: what to fix first, a fix prompt for your framework, and a re-check.
An accounting engine your AI connects to over MCP. Hand it bank and card statements, invoices, bills and receipts; get reconciled double-entry books with every number traceable to the page it came from. Requires a host that can reach files on your machine — Claude Code, Codex, Cursor, Grok Build, or Claude Desktop + Cowork. Browser chat can install it but cannot send files. Open beta; first 1,000,000 tokens free.
Connect your marketing accounts to Claude with one OAuth sign-in. 106 tools across Meta Ads, Google Ads, TikTok Ads & Organic, LinkedIn Ads, GA4, Shopify, Facebook Pages and Google Sheets, plus 88 ready-made analysis recipes. Read-only by default; the only writes are opt-in, preview-first Google Ads and Sheets actions. Flat pricing, no AI credits — 14-day free trial.
Prove you made it first. Blockchain Timestamp creative work via Claude or any MCP-enabled AI Agent.
Privacy-first web analytics, exposed to your AI agent as a first-class data source. The agent sees your traffic, referrers, geos, devices, live visitors, and custom events, and can reason across them. Ask what changed since the last deploy, why a campaign underperformed, which segment of signups actually activated, or have it build a conversion funnel and alert you when bounce rate spikes.
Pace is a remote MCP server that exposes wearable and fitness data to Claude via the Model Context Protocol. It connects to Garmin, Oura, Whoop, Polar, Fitbit and 20+ devices and provides 15 tools for querying sleep, activity, recovery, and training data. Hosted on Google Cloud Run, OAuth 2.1 authentication, Streamable HTTP transport. Instructions: First you need to create an account at: https://pacetraining.co and connect your wearables. After that you can connect the remote Server via Custom Connector in Claude and OAuth 2.1 Flow startet.
Agent-first data marketplace — AI agents search, purchase, and sell datasets via MCP.
Headless API-first double-entry accounting & bookkeeping engine. 84 MCP tools over HTTP.
Agent-first image hosting — upload images and get instant CDN URLs.
Someone to talk to, for your user: coaches, mentors, accountability partners. First session free.
- muninOAuthcom.getmunin
Open-source all-in-one MCP-first customer platform: KB, Conversations, CRM, CMS, Outreach, Analytics
