"Information about Python programming language or Python snakes" matching MCP connectors:
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Hosted remote server for a Microsoft 365, Gmail or IMAP mailbox you already own: read, search, draft, reply in thread, forward and file mail. It moves or flags up to 500 messages in one call, and a send leaves exactly one copy in Sent. A calendar is a separate connection, and connecting one adds diary and scheduling tools.
3DLogo.io, a browser 3D logo maker: 3D logos, 3D coins, 3D models from photos or prompts, embeds.
Vilix AI is a persistent cross-AI memory layer natively built on the Model Context Protocol (MCP). Connect once, and your memory, projects, decisions, preferences, and conversation history will follow you across all your favorite, and any other MCP-compatible AI tools: ChatGPT, Claude, Cursor, Codex, Grok, Perplexity, and more. While memory tools solve the problem of switching between apps, Vilix AI also solves the problem of switching between devices: continue your conversation on your phone, then pick it right back up on your laptop minutes later, with full context. Stores actual conversations, not just extracted facts, and has been engineered for long-term storage with years of context rather than days. Exposes get_context (what to say based on relevant memory to recall) and save_turn (what to persist) as core MCP tools, and full project, task, and skill management for agents to track what work is being done. Use cases include ChatGPT memory, Claude memory, Cursor memory, and AI agent memory in a shared layer for founders and developers who are using multiple AI tools and tired of having to re-contextualize everything every single time. OAuth-based setup with no tokens required, including a free tier. See https://vilix.ai/get-started for more information.
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.
The MCP server behind goodbotbad.bot, where the crowd rules AI transcripts good bot or bad bot.
Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.
Ask your AI assistant a cost question. Get allocation, correlation, and explanation in one response. Costory connects Claude, Codex, or Cursor to normalized cost data across AWS, GCP, Azure, Datadog, OpenAI, and Anthropic. https://costory.io Free trial 14 days, 250 USD / month up to 10M Spend
The CNAPS.ai MCP Server lets Claude build and run AI image, video, and text pipelines mid-conversation — no dashboard, no manual node-wiring. Describe a task in plain language (e.g. "upscale this photo 4x") and Claude selects the right model(s), wires a pipeline, and runs it.
Access Versium's B2B2C identity graph directly through your AI agent. Generate targeted lead lists, enrich records with contact and firmographic data, validate emails, and size audiences — all through natural language. No manual exports or API coding required. Requires an active Versium REACH subscription with API access.
Real-time web search with answer-ready results for Claude, Cursor and any MCP client. A Tavily alternative: same speed, 20.2% fewer tokens, higher answer quality (60.7% of decided duels won) on a public benchmark. Hosted on mcp.serpdive.com or npx serpdive-mcp.
Remote shell and detached long-running jobs on your own machines — no SSH, open ports or VPN.
LinkedIn data for AI agents: structured profiles, people search, companies, and posts over MCP or REST. 500 free credits, no card.
Manage CI/CD pipelines, debug failed builds, and optimize test suites directly from your AI tools and agents - no terminal required. The CircleCI MCP Server is a remote server hosted by CircleCI that connects AI tools and agents directly to your CI/CD pipelines, giving you a conversational interface to the same pipeline, workflow, job, and artifact data you'd normally reach through the CircleCI CLI or dashboard.
Real-time US business entity search across all 53 US jurisdictions - all 50 states, DC, Puerto Rico, and US Virgin Islands. Search, verify, and check the status of any LLC, corporation, or registered entity. Ideal for KYB, due diligence, and vendor verification.
A managed AI marketing agent that plugs into all your AI tools. Ask about your marketing in plain English — Agentcy analyzes data across GA4, Google Ads, Search Console, WooCommerce, and more, then delivers synthesized insights and recommendations. Not a data dump. Not a dashboard. An agent that thinks. Sign up at goagentcy.com to configure your domains and data sources. Free plan includes 50 requests/month — paid plans start at $29/mo.
Connect Claude, Cursor or any MCP client to AppSigma and let your AI research apps, read reviews and track rankings on its own – no glue code.
# **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.
Official hosted MCP server for Flicker (flicker.finance). Crypto, stock and FX market data (prices, screeners, funding rates, exchange stats, news), Flicker's published analysis zones and per-position assessments, plus the authenticated user's multi-exchange portfolio: positions, trades, balances and exchange connections, watchlist, alerts and notification preferences (watchlist/alerts/preferences are editable, everything else read-only). Does not place or manage trades. Streamable HTTP, OAuth r
AI-native form builder with a native MCP server. Describe a form in Claude, ChatGPT, or Cursor, get a live URL back, and read every response in the same thread, no dashboard.
Connect your AI assistant to iubenda to handle website legal compliance. Create and manage sites, generate privacy and cookie policies tailored to the services you use, add data-processing services from iubenda's catalog, set up cookie consent banners, and draft terms and conditions, all through natural language. Run cookie scans to detect trackers and update policies as your site changes. Built for founders, agencies, and developers meeting GDPR, ePrivacy, and US state privacy laws.
