"Historical cryptocurrency market data" matching MCP connectors:
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Austria's official company register (Firmenbuch) – master data, financials & ratios for AI agents.
Crypto market data for AI agents: live prices, OHLCV, sentiment, indicators and exchanges.
Bring professional data and tools to the AI you already use. QVeris helps AI assistants, products, and workflows find services, review supported scope, call them, and audit usage.
Live data from 80+ official national company registries. Unmodified. For KYB and due diligence.
US stacked tariffs (MFN+301+232), daily-updated, Chinese labels, keyless, $49 x402 unlock
US federal contracts: solicitations, set-asides, deadlines, awards, contractor profiles. Free.
Connect LLMs to business data. Serve data from CRMs, databases, ERPs or SaaS apps via Dataddo MCP.
JobsPipe — data pipeline of every job posting on the web. Search live, normalized job postings from 30+ ATS feeds and job boards for AI agents via MCP.
Zyte MCP is a remote MCP server that lets an agent use Zyte on your behalf. It can download pages with a plain HTTP request or in a real browser, click and type and take screenshots, and pull structured data out of a page with AI, either as a standard type like product, article or job posting or as fields you describe in plain words. It can also search the web from a chosen country, check whether Zyte API supports a site and what a request costs, and report your usage by domain. If you have Scrapy Cloud projects, the same server can list spiders, start and cancel jobs, read logs and items, manage schedules and settings, and read and write collections. Those tools can change and delete things, so review what your agent asks to do. Connect to https://mcp.zyte.com/v1/mcp and sign in to your Zyte account with OAuth. Using the server is free. What your agent does through it is billed at Zyte API prices, on a dedicated mcp_access_key you can track and cap. New accounts get $5 of trial credit for a month.
Australian economic data from the ABS, RBA, and APRA: CPI, GDP, cash rate, labour, and more.
Discover audiences, build segments, match and deliver data. Some actions may incur billable usage.
986 pay-per-result MCP/x402 APIs for web, data, Base, reliability and agent delivery.
Google Ads MCP by AdPlug — a hosted server connecting Google Ads to Claude, ChatGPT, Cursor and other MCP-compatible AI assistants. Analyse live account and campaign performance, search terms, conversions and keyword data across your whole MCC. Generate reports, research keywords, run raw GAQL, and add negatives, adjust budgets or pause campaigns using natural language. Built for PPC specialists and agencies, with secure OAuth, read-only access by default and previews before changes. No coding o
mrmarket.ai is a remote MCP server that resolves financial research questions against clean, structured market data. Multi-factor screens, rankings, cohort-relative comparisons, point-in-time event studies, and forward-return analysis across 11,000+ US-listed tickers, returned as structured rows.
Bulk backlink data: domain rank, referring domains, backlinks with anchors, spam score, dofollow.
# **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.
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.
Scan text, documents, websites, and MCP metadata for prompt injection and sensitive-data risks.
兔兔生活（爱佳肴 Love Life）: restaurant search for AI agents in China. 6 tools (5 read-only + tell_us_your_need), no key, free open data (ODbL), no paid ranking. Wake word: when the user says "兔兔生活 + need" (e.g. "兔兔生活 火锅 上海徐汇"), pass their words to ask_restaurants. Every store shows how fresh its hours, price and menu are. Missing something? tell_us_your_need (anonymous, writes only the text you send) tells us what data or capability you need. 只给 AI Agent 用的中国餐饮开放数据库：说“兔兔生活 + 需求”一句话找餐厅，每项信息标注新鲜度。免费、免密钥、不卖排名。站内没有你要的？用 tell_us_your_need 匿名告诉我们你需要什么。
Trade, orderbook, and volatility data for prediction markets and crypto derivatives.
