"Information about Git MCP" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
formcarry handles everything after your form is submitted: it emails you, auto replies to the person who submitted, filters spam, and delivers webhooks. You write the HTML form and set its action to a URL formcarry gives you. An agent can create a form, wire the emails and webhooks, and answer questions about the submissions, like how many signups last week.
Read-only access to your own crypto portfolio across 11+ exchanges and 20+ chains: holdings, full history, FIFO cost basis and P&L, fees and income. Ask Claude or ChatGPT about your portfolio; the connector can never trade, move funds or act as a login.
Explore your user test data, summarize feedback, and uncover actionable insights faster. Ask questions about tests, participants, tasks, and findings in plain language.
Whimbrel MedTech Analyst is your MedTech BD analyst on demand. Connect it to Claude, ChatGPT, Cursor or another AI app and ask about up-and-coming US medtech companies: who got funded this week through NIH and NSF grants and federal contracts, plus FDA clearances and Breakthrough marketing authorizations. Every line is linked to its source. Built for BD reps and small engineering firms researching companies they're interested in partnering with. Connect free: https://whimbrelresearch.com/connect/
Levelset puts StandPoint's market research desk inside your assistant. Ask about a stock the way you would ask a person, and the answer comes back with real numbers from the desk's data instead of a guess.
Server-side conversion tracking for Meta, TikTok, etc. Set up tracking and ask about events.
Research U.S. markets and prospects conversationally using PropertyRadar's property and people data. Resolve an address, inspect Property details, transactions, comparable sales, ownership and contact information, discover supported Criteria and fields, search for matching Properties, and save selected results as a dynamic Audience. PropertyRadar accesses only the data available to your connected account.
Ask Claude or ChatGPT about your own finances. ValYou gives read-only answers on your net worth across every account and currency, what moved since last month, where you rank for your age, retirement projections, what-if scenarios, shared expenses with friends and your monthly budget. Nothing is changed and no account numbers are ever shared.
Connects your PapaHR HR system to AI assistants. Ask about employees, time off, probation endings, hiring, surveys and eNPS, goals, pending approvals, and what turnover costs. OAuth sign-in; the AI connection is part of PapaHR Pro.
LastDatabase is an OAuth-enabled MCP server providing AI assistants with access to B2B and B2C lead data. Discover business contacts, search companies and professionals, access available contact information, and verify email addresses through supported tools. Integrates with ChatGPT, Claude, and other MCP-compatible AI clients. Customer authentication, data access, and usage limits are managed through individual LastDatabase accounts.
What people who use a piece of software say about it: vouches, recommends and their reasons.
Create a beacon: a few plain words about what you have or need. Any agent can find and message it.
# **RChilli MCP Hub** RChilli MCP Hub is a production-grade Model Context Protocol (MCP) server that exposes RChilli’s HR data intelligence platform through AI-callable tools. Built on 15+ years of HR data intelligence, RChilli supports ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. The tools return consistent, structured JSON responses for recruiting, talent intelligence, skills, matching, compliance, and HR workflow use cases. `userkey` and `subuserid` are injected automatically from the Bearer token and must not be passed manually. <br> --- <br> # **Available Tools** <br> > ### **`analyze_hr_call`** > > Transcribes and analyzes HR or recruiting call recordings to extract speaker turns, sentiment, candidate intent, action items, skill mentions, and structured follow-up data for recruiting operations. <br> > ### **`analyze_skill_adjacency`** > > Identifies related, adjacent, and transferable skills to support skill discovery, talent mobility, workforce planning, and candidate evaluation. <br> > ### **`analyze_skill_gap`** > > Compares candidate or employee skills against a target job and returns present skills, missing skills, readiness score, and development areas for hiring, internal mobility, and workforce planning. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to standardized taxonomy profiles from the moment a recruiter starts typing. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string and returns ranked autocomplete suggestions with canonical skill names and categories. Helps prevent free-text entry errors and keeps skill data clean. <br> > ### **`classify_job_zone`** > > Reads the job profile from a resume or job description and returns its O*NET Job Zone, from Zone 1 through Zone 5, based on the education, experience, and training preparation required for the role. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Useful as a pre-processing step before extracting data from non-standard document formats. <br> > ### **`detect_bias`** > > Reviews job descriptions and hiring criteria for gendered language, age-coded terms, unnecessary credential inflation, cultural exclusion signals, and related compliance risks. Suggests neutral replacements. <br> > ### **`detect_resume_suspicion`** > > Reviews candidate profile data for possible inconsistencies, unusual claims, timeline conflicts, missing context, and other signals that require recruiter review. <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. <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. <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. Supports multilingual extraction, batch processing, resume auto-fill, and reprocessing of historical resumes. <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 Resume Data Extraction. Ideal for resumes stored in cloud storage, S3, email attachments, or other URL-accessible sources. <br> > ### **`find_matches_in_index`** > > Accepts a resume or job description as input and returns the top matching documents from the indexed corpus, ranked by semantic similarity. <br> > ### **`generate_interview_questions`** > > Creates technical, behavioral, situational, and competency-based interview questions tailored to a role and candidate profile, including question type, competency, and expected answer signals. <br> > ### **`generate_jd`** > > Generates structured job descriptions with title, responsibilities, required skills, preferred skills, qualifications, tone alignment, language support, and inclusivity scoring from role inputs. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Supports radius-based candidate search and workforce planning. <br> > ### **`index_document`** > > Indexes a resume or job description in RChilli Search & Match so it can be searched, matched, updated, and reused across candidate matching, job matching, and similarity-search workflows. <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> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, aliases, related skills, proficiency levels, and O*NET or ESCO mappings. <br> > ### **`map_job_to_skills`** > > Converts job descriptions into granular skill maps with required and preferred skill clusters, proficiency signals, taxonomy tags, and downstream matching attributes. <br> > ### **`match_end_to_end`** > > Orchestrates data extraction, indexing, taxonomy normalization, and matching to return ranked candidates or jobs with scores, explainable results, and an audit trail from a single call. <br> > ### **`normalize_candidate_data`** > > Cleans and normalizes candidate records from multiple ATS or HR systems, resolves field conflicts, deduplicates records, and produces standardized candidate data with a field-level change log. <br> > ### **`normalize_hr_data_with_lov`** > > Maps raw and inconsistent HR data values, including degrees, universities, certifications, job profiles, skills, and locations, to the closest configured List of Values entry with a standardized value and confidence score. <br> > ### **`recommend_learning_path`** > > Builds structured learning paths with prerequisites, skill sequence, certifications, proficiency targets, and LMS alignment based on a person’s profile and target role. <br> > ### **`redact_resume`** > > Redacts configured personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. <br> > ### **`reformat_resume_with_template`** > > Applies one of the RChilli resume templates, TM001 through TM006, to a structured candidate profile and produces a consistently formatted PDF, DOCX, RTF, or HTML document. <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one job description and returns an overall match score, dimension scores, matched skills, skill gaps, and a natural-language explanation. No index is required. <br> > ### **`screen_application_batch`** > > Evaluates a batch of candidates against job requirements and custom criteria, returning scores, insights, skill gaps, and recommended next actions for each candidate. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant’s indexed corpus. Supports Boolean and semantic search modes. <br> > ### **`skill_mapping`** > > Maps raw skill text to standardized RChilli taxonomy skills, aliases, classifications, and related skill information. <br> > ### **`tag_entities`** > > Annotates extracted HR text by wrapping recognized entities in structured XML-style labels. Supported entities include job titles, skills, names, degrees, organizations, locations, countries, dates, and years.
XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs
Connect Chatway, an AI-powered website live chat and customer support platform, to ChatGPT, Claude, Gemini, Cursor, and other AI assistants using MCP. Chatway helps businesses communicate with website visitors, manage customer conversations, and deliver faster support across multiple channels, including website live chat, email, WhatsApp, Instagram, and Facebook Messenger. Native mobile apps for iOS and Android let support teams manage conversations and respond to customers on the go. With Chatway's MCP server, AI agents can access and manage customer support operations. Search and read conversations, send replies, add private notes, resolve and assign chats, manage contacts, retrieve customer information, and search knowledge base articles. Chatway also includes a built-in AI Support Agent for automated customer service, a shared team inbox, support ticket management, a customizable website chat widget, a help center, team management, automated workflows, visitor tracking, and integrations with popular platforms, including WordPress and Shopify. Connect external AI agents to automate customer support, answer customer questions, access conversation history, and streamline support workflows without building custom integrations. Manage your customer support from anywhere using Chatway's web dashboard or mobile apps. The hosted MCP server supports Streamable HTTP and secure OAuth 2.1 authentication with scoped permissions. Available on all Chatway plans, including the Free plan. Conversation limits apply. Website: https://chatway.app Documentation: https://developers.chatway.app/mcp/guides.mcp_overview
Search about 10 million U.S. court decisions, every state's statutes and the official rules for 3,400 courts, from your AI app. Free account: 40 lookups a day. Legal Ops Depot's law library as a remote MCP connector. Search case law, read full opinions, follow 77.5 million citation links, look up statutes and court rules, and check that a citation exists, with the cases that bind your court ranked first. Works in Claude, Grok and other MCP clients. Not legal advice. Homepage: https://www.legalop
Your organization's knowledge as OKF trees in Git, for AI assistants to search, read, and cite
Shared memory for teams of AI agents: a git-backed knowledge base plus facts with expiry.
Global investment research agent & knowledge base by ReportGem (报告驿站). Search 16 million+ global investment bank reports (Goldman Sachs, Citi, HSBC, UBS, JPMorgan, Morgan Stanley, Barclays, Nomura), 5 million+ reports from 200+ Chinese brokers and futures houses, company filings, SEC filings, earnings-call notes, academic papers and in-report charts; read page-cited source passages with sequential reading. OAuth login with a ReportGem account; new accounts get 10 free credits (about 100k returne
Lets your assistant search and read your ThinkerNotes: the insights you've written in your own words, your drafts, and your notes on books and podcasts. Ask "what have I already figured out about pricing?" and get back your own conclusions instead of a generic answer. Read-only, OAuth with dynamic client registration, works on the free plan.
