"Information about Visual Studio Code (VSCode)" matching MCP connectors:
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Search public open-source code, documentation, metadata, vulnerabilities, changelogs, and examples.
Ask your AI assistant about your own website's SEO and get answers from your real data, not generic advice. One connector, all your channels: Google Search Console (rankings, clicks, indexing), Google Analytics (traffic and sources), Google Ads (campaigns and search terms), Google Business Profile (local visibility and reviews), Google Trends, keyword research, backlinks and link prospects, competitor rankings, site crawls, and AI visibility (does ChatGPT mention your site?). Ask things like: which keywords am I one push away from page 1 for? Why did traffic drop last month? Which competitor is outranking me, and where? Are my ads and SEO fighting over the same keywords? Then let it act. On a paid plan, your assistant can prepare SEO fixes, content campaigns, and article drafts. Nothing touches your site until you approve it in SEOmatic, and every change shows before-and-after results. Connect via OAuth: log in, pick your site, done. No API key needed.
Connect your AI assistant to Onsomble to track how ChatGPT, Claude, Gemini and other AI assistants talk about your brand and market. Set up AI visibility scans, review visibility, Share of Voice, sentiment, narratives and cited sources, and manage recommendations in conversation. Requires an Onsomble account.
Scores code against a repo's own incident history, rolled into an 8 index Production Reliability Index (PRI). Exposes suggest_code, save_recommendation, and get_scan_report as tools.
Verify identities, screen for AML/PEP risk, and detect fraud across Africa, Asia, Europe, and the Americas — directly from your AI assistant, with no custom integration code required.
Compliant invoicing for freelancers: create, issue and track invoices from your AI agent.
Search and load AI agent skills. Free metadata; full content requires a Pro or Studio account.
Build product adoption your way - Product adoption infrastructure no-code or all-code.
IconScout MCP lets AI coding tools like Claude, Cursor, VS Code, and Devin pull icons, illustrations, 3D assets, and Lottie animations directly while building. The difference from plain asset search is that it picks assets that match the style of the site or UI you're working on, so everything stays visually consistent.
Review and rewrite LangChain, LlamaIndex, Ollama, and XRPL code against current APIs.
Compliance frameworks delivered to AI agents. Nizh gives your agent read access to your organization's compliance program — SOC 2, ISO 27001, CMMC 2.0, NIST, and more — as MCP tools, so it can check posture, read a control's objectives before changing code, and record where evidence lives.
Connect your AI assistant to your Peec AI account to monitor and analyze your brand's visibility across AI search engines like ChatGPT, Perplexity, and Gemini. Ask questions about brand visibility, competitor comparisons, source citations, and trends: all in plain language, directly from your AI tools.
Visual AI prompt builder that decomposes any raw prompt into 12 semantic blocks (role, context, objective, constraints, examples, etc.) and recompiles them into Claude-optimized XML. Exposes decompose_prompt and compile_prompt tools.
# **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.
Nephia is a brand monitoring service, and this is its remote MCP server. Claude, Cursor, ChatGPT or any MCP client can read the mentions your brand gets on 14 sources: X, Reddit (posts and comments), YouTube, TikTok, Bluesky, Hacker News, Mastodon, Lemmy, GitHub, Product Hunt, Stack Overflow, any RSS feed, Vinted, and AI answers from ChatGPT, Gemini and Perplexity. Every mention arrives already read, with its sentiment and intent, so an agent can answer plain questions: which complaints came in since Friday, what Reddit said about us this week. The source is an argument, not a tool, so one call reads every source you watch. Sign-in is OAuth in the browser: no API key to copy. The consent screen has three permissions: read your mentions and Queries, change what is running (pause, resume, retire), and spend credits (semantic search and AI passes), which arrives unticked. Every tool description states its cost, so a model can budget before it spends. The server is on every plan, Free included, and reading your own mentions through it costs nothing.
Join.cloud is Slack for AI agents. Create rooms, invite agents, and let them collaborate in real-time. Agents communicate via broadcast messages or DMs, and each room is a standard git repository for code collaboration (clone/push/pull).
Scan text, documents, websites, and MCP metadata for prompt injection and sensitive-data risks.
Your agent needs markets — prices and fundamentals for listed companies, the filings behind them, crypto, and what the prediction markets put the odds at. **What you can ask for** • "Pull this company's income statement, cash flow and balance sheet for the last 8 quarters." • "What did insiders buy or sell, and when?" • "Snapshot prices for these 50 tickers, then the OHLC history for the three that moved." • "What are the current odds on this event across Kalshi and Polymarket?" • "Screen for companies matching these financial criteria." **How to use it** Point any MCP client at https://mcp.aisa.one/finance/mcp and sign in with OAuth — there is no key to create or paste. 49 tools: prices and snapshots, income statements, balance sheets and cash flows, metrics and ratios, earnings and analyst estimates, filings and line-item search, insider trades, macro interest rates, news, a screener; CoinGecko spot prices, market tables, OHLC, per-venue tickers and trending; Kalshi and Polymarket markets and trades; plus EDINET filings for Japan. **Why this rather than the source** Equities, crypto and event markets behind one account, so a cross-asset question is one conversation. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Read the number here, then ask the same agent what X is saying about the ticker today — 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/marketpulse/mcp · /crypto-market-data/mcp · /prediction-market-data/mcp · /stock-pulse/mcp for one slice each.
AgentiSend is a transactional email API: send through verified domains with a message log, budgets, a preflight and refusals that name the fix; built so AI agents can send on your behalf. The hosted MCP server at https://api.agentisend.com/mcp exposes 82 tools (44 on tools/list; the rest via list_more_tools). A send is one message or a batch of up to 500 items with per-item results. preflight_email runs every gate a real send runs, sends nothing, and costs nothing. Every 4xx returns code, message, and fix. There is no tool for unsolicited mail. Auth is a bearer API key or OAuth 2.1 with dynamic client registration. Starter prompts: "Send this receipt to the customer." "Preflight this send and tell me what would stop it." "What can I spend today?"
Onymu is an MCP server for domain name search, domain availability checking, and social media username lookup. Check a domain name against hundreds of TLDs in one call, including .com, .io, .ai, .co, and country-code extensions. Generate brandable startup names, business names, and product names from a keyword, and instantly see which ones are still available to register. Check username availability across major social networks so a brand name comes with matching handles. Save domains, set favorite TLDs, and recall recent searches to keep name research organized across sessions.
