"Maps" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
One key and one prepaid balance for the live data AI agents need: Google search results, keyword and SEO data, Google Maps places, e-commerce product prices and exchange rates. Agents find tools by job, see the price before running, and pay per call. Failed calls are free. Sign in with OAuth, no API key to copy. Early access: new accounts are approved in batches.
Google SERP, keyword volume, tech stack, rank tracking, backlinks, site audits. Pay per use.
Google Maps places, reviews, contributor history, photos and posts as JSON. No Google Cloud.
ChatGPT visibility, SERP, Maps, reviews, traffic, backlinks, tech stack, PDF tables, Amazon, jobs, Trends.
Public web data as clean JSON for AI agents: Google, Amazon, TikTok, Instagram, YouTube, LinkedIn, Google Maps, Reddit, Zillow and hundreds more websites. One API key, pay per call, failed calls are free.
Local SEO MCP: Google Maps rankings, Google Business Profile ratings and review counts. Google Maps positions for a keyword in a city with rating, review count, category and address, and a business's Google Business Profile with rating distribution and claimed status. Use for point-in-time Google Maps rankings and Google Business Profile lookup by location. This focused SEO Data subset returns rating and review-count summaries, not full review text, review replies or Business Profile management. Billing: paid data calls use API credits; get_api_credit_balance is free. The focused connections and SEO Data use the same balance and prices. Example prompts: - Check Google Maps results for 'running shoe store' in the city I specify after I approve the API-credit cost. - Within my approved API-credit budget, compare Maps rankings for the same keyword in two specified places. - After confirming the API-credit spend, retrieve the business profile I specify and summarize its rating and review counts, not review text. Docs: https://docs.crakseo.com/mcp-servers/local-seo
# **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.
Google search, news, maps, webpages, cited answers, research and ChatGPT/Gemini answers for agents.
Google SERP API MCP: live Google, Bing, AI Overview and Google Maps results as JSON. Pay per call. Live search engine results pages as structured JSON: Google organic results with SERP features and AI Overview sources, Bing results, Google Maps local results, and live Google rank checks for a domain across up to 10 keywords. Use when an agent needs live Google or Bing search results for a keyword, country, language and device. This is a focused subset of SEO Data, not an additional required connection or a scheduled monitoring service. Billing: paid data calls use API credits; get_api_credit_balance is free. The focused connections and SEO Data use the same balance and prices. Example prompts: - Show the top ten Google results and SERP features for 'trail running shoes' in the US, after I approve the API-credit spend. - Compare Google and Bing results for my keyword in the same market, within my approved API-credit budget. - After confirming the API-credit cost, report which source URLs Google's AI Overview cites for my keyword. If none is present, say so. Docs: https://docs.crakseo.com/mcp-servers/serp-api
SEO data MCP: SERP, keywords, backlinks, live rank checks, page audits, local and AI checks. Every SEO data tool in one server: Google and Bing SERP results, live rank checks, AI Overview sources, keyword search volume, ideas and difficulty, backlinks, referring domains and anchors, ranked keywords, competitor domains and keyword gaps, site audits with Lighthouse scores, Google Maps rankings, Google Business Profiles, and ChatGPT and Perplexity brand mentions. Start here for paid SEO research with one connection. Includes all seven focused SEO data servers' tools at the same prices and from the same API-credit balance; do not connect both for duplicate results. Search Console reporting and URL Indexing are separate connections. Billing: paid data calls use API credits; get_api_credit_balance is free. The focused connections and SEO Data use the same balance and prices. Example prompts: - After I approve the API-credit cost, compare US search volume and difficulty for 'trail running shoes' and 'running shoes for flat feet'. - For the domain I provide, check its backlink summary, referring domains and anchor texts after confirming the API-credit spend. - Compare live Google positions and competitor keyword opportunities for my domain and keywords, within the API-credit budget I approve. Docs: https://docs.crakseo.com/mcp-servers/seo
Web scraping for agents. Point it at a URL and it returns the page as clean markdown, JavaScript-rendered pages included. Point it at a site and it maps the URLs or crawls the section you need in the background, a few pages at a time so results fit in the conversation. Search the web and read full pages, extract fields with a JSON schema you define (validated, never invented), read a store's catalogue or a blog's posts from the platform's own feed, and check whether a page has changed. Failed requests cost nothing. The free plan includes 1,500 credits a month.
Advantage-play guides for 360+ casino slot machines: what to look for on the machine and when it's worth playing. Search machines, read free overviews, and get five full guides free. Other guides and photo reads are $1.99 each through Stripe machine payments. Members who sign in at https://slotmaps.com/mcp/account get every guide included.
Find local businesses on Google Maps, Yellow Pages and Yelp, then pull emails and phones from sites.
Hosted MCP server exposing 319 structured public web-data tools across search, maps, commerce, social, finance, travel, app stores, and reviews — each returning clean JSON. Free 2,000 credits/month.
Search and read public data from X/Twitter, Reddit, YouTube, Instagram, TikTok, Facebook, Threads, Bluesky, Trustpilot, Amazon, Google Maps, news, forums and the web. 90+ read-only tools plus ready-made research playbooks (lead finding, brand monitoring, review mining). Hosted: connect with an API key; 50 free requests per endpoint each month.
Your agent needs the Google results page as it actually renders — organic and paid, the AI overview, maps, images, news, jobs and the finance panel — not a scraped guess. **What you can ask for** • "What does the SERP for this keyword look like in Germany, on mobile?" • "Does this query trigger an AI overview, and what does it say?" • "Who is advertising against our brand name?" • "Find local results and the map pack for this phrase." • "Search Google by this image and tell me where else it appears." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-serp/mcp and sign in with OAuth — there is no key to create or paste. 38 tools across Google's surfaces: organic, ads and advertisers, AI mode, autocomplete, images, news, maps and local, events, jobs, datasets, scholar, finance quotes and markets, plus Semrush's organic and paid result sets. **Why this rather than the source** Location and language are parameters, so you can read the page a customer in another country sees. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Read the SERP here, then ask the same agent who links to the winner or how much traffic they get — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/seo-serp-other-engines/mcp for Bing, Yahoo, Baidu, Naver, Seznam and YouTube. https://mcp.aisa.one/seo/mcp for all of it at once — rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
Global earthquake events from the USGS, 2150 BC-present: magnitude, depth, location, counts.
Global volcanic eruptions from the Smithsonian Global Volcanism Program: VEI, location, dates.
26 authless MCP servers: flights, stays, maps, shopping, web search, Polish web (Allegro, OLX, NBP).
Domain/IP, web capture, Google search/maps, YouTube, Instagram, TikTok, X and Amazon data jobs
Find businesses by what they are and where they are, collect a whole city, and export the list.
Real Google and Google Maps SERPs for AI assistants: pixel positions, AI Overviews and sources.
B2B leads from your AI assistant: LinkedIn, verified work emails, Crunchbase, PitchBook, Google Maps, stores, creators. Pay per result.
Google, Bing, DuckDuckGo and Google Maps search results, free without an API key.
Scraping API for Google Search, Maps, Flights, Jobs, YouTube, LinkedIn, Trustpilot and more.
Read Alkemata articles and maps; submit reviewed proposals; create map content with authorization.
Search Google Maps businesses via MCP - name, address, phone, rating, hours, GPS.
31 pay-per-result web data tools: LinkedIn, Google Maps, SEC, real estate, jobs, leads, gov data.
Ground your AI applications with trusted geospatial data from Google Maps.
The Google Maps MCP server is a fully-managed server provided by the Maps Grounding Lite API that connects AI applications to Google Maps Platform services. It provides three main tools for building LLM applications: searching for places, looking up weather information, and computing routes with details like distance and travel time. The server acts as a proxy that translates Google Maps data into a format that AI applications can understand, enabling agents to accurately answer real-world location and travel queries.
