"Features of Grid Trading Strategies" matching MCP connectors:

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. Use Cases Resume screening — Parse and structure resumes for AI-powered shortlisting Job description analysis — Extract required skills, experience range, and qualifications from any JD Candidate-to-job matching — One-to-one fit scoring with field-level evidence, no indexing required Talent pool search — Keyword search across your indexed resume database Skill gap analysis — Identify what a candidate is missing for a specific role Bias-free hiring — Redact names, photos, gender, and age before sharing with hiring managers Taxonomy enrichment — Look up and autocomplete 10,000+ standardized skills and job titles Document standardization — Convert and reformat candidate documents into consistent templates Tools — 17 Total userkey and subuserid are injected automatically from your Bearer token — you never need to pass them manually. 🔍 Resume & Job Description Parsing — 3 tools 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). 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. 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. 🧠 Skills & Job Taxonomy — 4 tools 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. 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. 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. 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. 🛡️ Redaction, Documents & Utilities — 7 tools 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. 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. 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. 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. 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. 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. classify_job_zone: RChilli's Job Zone Classification tool reads the job profile from a resume or job description and returns its ONET 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 ONET. 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. 🎯 Search & Matching — 3 tools 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. 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. 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.

Connect your AI assistant to Signed and ask about your angel investing in plain English: how the portfolio is doing, what distributions came in this year, what’s sitting in the pitch queue. It's a view into the startups that you've invested in (or are thinking of investing in!)

AI-agent web search, answer-ready content. Beats Tavily: 60.7% of quality duels, 20.2% fewer tokens.

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.

DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.

Inventory of your service accounts, kept current by your coding agents. Metadata only, no secrets.

Remote MCP server for address-level civic data: FEMA flood zones, municipal 311 density trends, ACS census demographics, and address search. Same tools for every supported city (Montgomery AL and Baltimore MD live).

Connect any AI agent to the NachoNacho marketplace with the Model Context Protocol MCP Let your AI search thousands of B2B SaaS AI products, compare deals, and sign up — all from chat

SoupNet gives your AI agents one shared memory of how you think — across Claude, Cursor, and ChatGPT. Each checks your past decisions as searchable “recipes” and acts on your real judgment. Share it, and your team’s agents inherit that judgment too.

Polymarket intelligence, whale tracking, anomaly detection, copy trading, and paper trading for AI agents.

Institutional-grade financial data at a fraction of the cost, built for individuals and AI agents.

Persistent memory for AI agents. Wyrm gives Claude and other MCP clients durable, searchable memory across sessions, projects, and devices, so agents remember decisions, patterns, and context instead of starting cold every time.

Lexicon Oracle is a deep-knowledge engine that analyzes population data and professional behaviors unavailable in standard LLM training. Beyond raw demographics, it specializes in predictive modeling for newer generations (Gen Z/Alpha), identifying emerging cultural trends, and forecasting the success probability of new business ventures based on behavioral market fit. Key Capabilities: Predictive Success: Forecasts business viability and market adoption. Generational Intelligence: Deep-dive ana

The only News based AI MCP your agents will ever need — custom categories, global regions, and time-scoped results in one tool. We use multi-vector & sparse-hybrid search to search through thousands of articles across the world to find the exact news you're looking for.

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.

Search Parliamentary questions and motions from UK House of Commons

Open-source MCP server that gives AI agents access to real email and calendar in one npm install. Solves the problem of AI agents hitting a wall when they need your inbox.

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

Get realistic term life insurance rates from the CoverSavvy Term Life Index. Query monthly premiums by age (20-65), gender, health class, coverage ($100K-$4M), and term length (10-30 years). Rates are averages of 2-3 lowest carrier quotes from leading U.S. life insurance carriers.

Remote MCP server implementing the Streamable HTTP transport with 25 tools for AI assistants. Enables programmatic management of multi-platform content publishing — create posts, run automations, manage RSS feeds, generate hashtags, search images, and publish to 13+ platforms (Instagram, LinkedIn, X, WordPress, etc.). Authenticated via Bearer token.