"Information about Prisma" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Connect AI agents to Emitd email sending, message tracking, templates, and automations. Emitd hosts a Model Context Protocol server for integrating supported email operations into AI-agent workflows. Connect a compatible client to the hosted endpoint (https://mcp.emitd.com/mcp) and authenticate with an Emitd API key. Available tools depend on the key's permissions and enabled features. Emitd's capability areas include sending email, message activity, templates, contacts, audiences, segments, domains, analytics, inbound email, broadcasts, automations, webhooks, and suppressions. Use restricted keys, sending guardrails, and approval settings appropriate to each workflow. For more information check https://emitd.com
PrismPoster Studio connects your assistant to your own PrismPoster account, so you can make media without leaving the chat. Video: videos with sound, from words or a picture. You can change a video, extend it, or sharpen it to 4K. Images: new images and edits to existing pictures. Characters: consistent characters saved as @tags and reused across everything you make. Remake: put yourself, a described character or a consenting friend through the exact moves of a clip or a Trend.
Ask about your business's sales, Google rankings, AI visibility and email marketing, and have Kooga write, change and send for you, asking first before anything leaves Kooga.
Server-side conversion tracking for Meta, TikTok, etc. Set up tracking and ask about events.
PGxAI Andromeda is an educational reference tool for exploring published drug-drug interactions, gene-drug associations, and drug-disease interactions. View relevant excerpts from FDA drug labeling and other referenced sources, with links to the original documents. Learn about documented interactions and how genetic variants and metabolizer phenotypes relate to drug metabolism.
Climate and disaster risk for any place or property: flood risk, heat waves, storms and hurricanes, wildfires, earthquakes, sea level rise and 7-day weather risk. Is it safe to go there? Ask about any city, address or coordinates and get this week's weather risk (heat, cold, wind, heavy rain, snow), wildfires, earthquakes, floods and cyclones happening nearby right now, long-term exposure to 2050 and 2080 (flood depth, sea level rise, extreme heat, drought, water stress) and the country's disaster-risk profile and rank among 194 countries. Also compares and ranks countries by risk for ESG and insurance research, and in Claude and other MCP Apps hosts shows an interactive map of the place right in the chat. Every value cites its source: INFORM, ND-GAIN, World Bank, CMIP6, ERA5, IPCC AR6, WRI Aqueduct, GDACS, NASA FIRMS, OpenAQ, ECCC GDPS. Remote, free, no API key, read-only.
Look up Swedish name days by date or name. Find out which names are celebrated today, discover the names associated with any calendar date, or find the name day for a specific name. The service provides Swedish name day information, including name meanings, cultural and historical background, alternative spellings, and name variants.
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
Ask questions about Claude Code, Cursor, Codex and MCP — get answers grounded in their official docs, with citations. A hybrid RAG service that AI agents call through two MCP tools (or over REST). It indexes ~600 pages of official documentation, refreshes itself daily, and every design choice is backed by an experiment.
# **RChilli** 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.
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
ParseHub.dev is a hosted document-to-records service with a remote MCP server. Agents can upload a CSV, PDF, or Word file, summarize and analyze CSV data (filter, sort, group_by, and more), read text from PDF and Word files, extract attendees, agenda items, and action items from meeting notes, ask a question about an uploaded document, and store files as database records to list and read later. Each account sees only its own files and records. **Endpoint:** `https://parsehub.dev/mcp` (Streamable HTTP, stateless) **Auth:** API key in the `X-API-Key` header (keys start with `mcp_`), or `Authorization: Bearer <API key or JWT>`. Every request without credentials returns 401. **Plans:** Free (100 API requests/month, 1 document upload), or 5,000 requests/month on the $9/month or $42/year plan. Every MCP request counts toward the allowance. **Tools:** upload_csv, summarize_csv, analyze_csv, upload_document, read_document, extract_meeting_notes, ask_document, database_status, list_database_documents, get_database_document, store_document, extract_stored_meeting_notes, export_database (administrators only). Not affiliated with ParseHub (parsehub.com), the web-scraping tool. ParseHub.dev does not scrape websites. By Poietes LLC. Docs: https://parsehub.dev/guide#connect-via-mcp
Paw to paw. Shelter pets, one question away. Ask in plain words, in any of ten languages ("Use Petnecto to find me a calm older dog near Seattle that is good with cats") and get real adoptable pets near the place you name, with photos, ages, sizes, what each rescue says about them, and exactly how to reach the rescue. Listings come from open public data that shelters and governments publish (Taiwan's national adoption listings, King County WA and Montgomery County MD in the US, Zaragoza and Vienna in Europe), credited in every answer. Adoption always happens through the rescue: Petnecto takes no payments, applications or personal details, and needs no account.
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.
Deterministic, cited regulatory research for product launches; legal information, not legal advice.
Ask AI about Simpro, Xero, Deputy, Employment Hero, Dialpad, ELMO, Moveware and fleet data you own.
Christian discovery for AI assistants: read any Bible passage word for word from a stored public domain King James text (never generated), find verses for what someone is carrying, get honest answers about Jesus and faith from Scripture, and find real churches, prayer gatherings and Tables near any city in the world. Every Scripture answer carries an evidence label: translation, corpus version and a content hash. Read only and free for everyone. Everything points to Jesus Christ.
Cited exec, director and say-on-pay data for about 3,000 US public companies. Free tier, no card.
ScanSing reads printed sheet music. Give Claude a PDF or a photo of a score and it gets back MusicXML, the format MuseScore, Sibelius, Finale and Dorico open. It is the recogniser inside the ScanSing app for choir singers, offered as a connector. Once a score is recognised, Claude can answer questions about it without recognising it again: - what the key, time signature, tempo and length are, and each part's range, clefs and lyrics; - one voice on its own, for example just the alto line of a choir piece; - the score or a part moved to another key, with notes respelled for the new key signature; - a MIDI file, one track per part, to listen to or rehearse with; - a short-lived download link to open the result in a browser or notation app. It handles PDFs up to 40 pages and PNG, JPEG, HEIC, TIFF and WebP images, can recognise selected pages of a long PDF, and can split a songbook into one MusicXML per piece. A file can be given as a web link or a small image; in Claude Code, a file on your computer is sent through a one-time upload link. Recognition spends pages from your ScanSing plan, so it is the only tool that is not read-only. Everything else works on the stored result and is free. The first connection with a new email comes with 20 free pages; paid plans start at $9 a month for 300 pages. Scores and results are deleted about an hour after recognition and are never used for training.
