"Google Pub/Sub" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Google Vids: Gemini Omni video, talking avatars from a photo or description, speech, extend, upscale
Account-less MCP access to 45 Gemini models & autonomous agents via L402, x402, and MPP.
Google Gemini Notebook (NotebookLM): notebooks, sources, cited chat, podcasts, video, slides
Is your brand named by ChatGPT, Claude, Perplexity, Gemini and Google AI? A yes or no per question.
Google Flow's agent: chat that plans and makes images and videos, approvals, your own media
LLM API prices and AI agent cost estimates, verified daily. Read-only cost lookup tools.
EasyGerber brings AI printed circuit board (PCB) design, layout, and routing to MCP-compatible assistants. Describe a circuit or start from firmware pin assignments, search published electronic components, and build schematics using catalog parts with their footprints and available 3D models. Create and revise boards, generate layouts with automatic component placement and routing, inspect previews, and check saved layouts for blocking design issues. Export manufacturing ZIPs containing Gerber and drill files, a bill of materials, and component placement data, or download an editable EasyGerber (.egb) file. Start without signing up. Your agent creates a private guest session for one board, including catalog access, edits, layout, checks, previews, and exports. Sign in through OAuth to work with saved account boards, access permitted organization boards, or save the guest design to your account. Guest support depends on your MCP client and installed integration.
Google Flow Music (Lyria): songs, lyrics, extend, cover, remix, effects, stems
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.
# **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.
Ask how ten AI engines (ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, AI Mode, Copilot, Grok, DeepSeek, Meta AI) describe a brand, which sources they cite and how that changed, then build white-label client reports from the same data. 74 tools; every write is shown as a preview first and needs a second, confirmed call.
Is your brand mentioned and cited in ChatGPT, Perplexity, Gemini and Google AI answers?
AI visibility (GEO): how ChatGPT, Gemini and Google AI talk about your brand, with an action plan.
AI visibility for your brand: which buyer questions name you in ChatGPT, Perplexity, Claude and Google AI Overviews, which competitors AI recommends instead, which sources it cites, and what to fix first. OAuth sign-in with email and a one-time code.
What ChatGPT, Gemini and Google answer — structured JSON with cited sources.
AutomateLab Citation Intelligence checks which URLs Perplexity, Claude, ChatGPT, Gemini, Bing, and Google AI Overviews cite. Self-hosted, with your own API keys. Documentation: https://automatelab.tech/products/mcp/citation-intelligence/
Publish the apps you build with AI and share them like a Google Doc, with data, files and AI.
clariBI is an AI-powered business intelligence platform built for small and mid-sized SaaS, ecommerce, and operations teams. Instead of writing SQL or building dashboards manually, users ask questions in plain English ("what's our CAC by channel last quarter?") and the AI engine pulls the data from Stripe, HubSpot, Google Analytics, ad platforms, Jira, and 30+ other sources via the open Model Context Protocol. Dashboards generate themselves on source connect.
Look up how any brand surfaces in ChatGPT and Google AI Overviews. Brands, prompts, sources, niches & more.
Scores whether a business's Google Maps reviews are genuine. Your agent collects them, we judge.
Compare LLM API and cloud compute pricing, estimate workload costs, pick a model within budget.
Compare GPU rental prices per hour on AWS, Azure, Google Cloud and Akash, by chip, with free GPUs.
Typed AI decisions for agents: classify, route, screen evidence, score and batch-label text.
See whether ChatGPT, Google AI and Perplexity name your business, and get the fixes applied.
Daily ranks of consumer AI apps across the App Store and Google Play. Read-only, ranks only.
Search 1,000+ practical AI use cases by industry and workflow, with AI consulting services.
Free AI visibility checks, then see if ChatGPT and Google AI name you or your competitors instead.
Sub-5ms topological 4D associative memory coprocessor for LLMs and multi-agent swarms.
Search robot code and exact-version findings; check evidence before preparing with the Hub CLI.
How ChatGPT, Gemini, Perplexity and Google AI name your brand, cite sources and rank rivals.
