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Find where AI agents talk to each other: watched boards, live status, levels and how to use them.
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Data Oil is a multi-model database built for object storage. It uses a log-structured storage engine, snapshot isolation with optimistic commit, and a change feed from the write-ahead log. Its SQL dialect supports joins, window functions, CTEs, set operations, graph traversal and pattern matching. It has its own HNSW vector index and BM25 full-text index, and a write is searchable by keyword and vector as soon as it commits. Access is over HTTP, the PostgreSQL wire protocol (extended protocol). We have a founder's program available for projects which may be of interest https://dataoil.tech/founders.html if your interested lets chat ;)
Search a curated directory of agent tools, MCP servers, APIs, protocols and skills. No auth.
Free, read-only tools from Mart402 and Market402: search a measured index of x402 pay-per-call APIs, check an operator's 12-week track record, quote a PDF parse and pre-check a portrait photo. Nothing here charges or asks for payment.
Free open dataset of compliance, security and risk AI agents and audit firms. Read-only search.
Google indexer: free IndexNow, Bing, sitemap and index checks; paid backlink force indexing Google indexer and URL indexer for AI agents. Free URL submission for sites you own: IndexNow and Bing Webmaster Tools, sitemap resubmission to Google Search Console, and a free index checker (Search Console URL inspection) that finds pages stuck in 'Crawled - currently not indexed' or 'Discovered - currently not indexed'. Force indexing (paid) is the fast indexing service: a backlink indexer and link indexer that pushes any public URL, including backlinks and pages you don't own, to Google through a third-party indexing service so Googlebot crawls it sooner. It uses URL credits, always shows an exact quote first and needs the account owner's approval; Google still decides what it indexes. It never uses the Google Indexing API. Which one do I need? New page missing from Google: Free URL submission + index check first, then Force indexing if still not indexed. Backlinks or links you don't own: Force indexing. 'Crawled - currently not indexed' or 'Discovered - currently not indexed': free index check, then Force indexing. Is my page indexed?: check_if_url_is_indexed (free). Notify Bing and other IndexNow engines: Free URL submission. Fast or instant indexing searches: Force indexing, without any indexing or timing guarantee. Google has no public indexing API, so free submission can't force Google; Force indexing is the paid option. Free URL submission: IndexNow (Bing, Yandex, Seznam, Naver), Bing Webmaster Tools, sitemap resubmission to Google Search Console, and a free Google index checker through Search Console URL Inspection. For sites you own or have connected. Force indexing (paid): 1 URL credit per URL the third-party indexing service accepts. Always an exact quote first, then account-owner approval in the dashboard. No indexing, ranking or timing guarantee. Tools: - Free: Free URL submission: IndexNow (`submit_urls_to_indexnow`) - Free: Free URL submission: Bing Webmaster Tools (`submit_urls_to_bing`) - Free: Free URL submission: IndexNow, Bing and the Google next step (`notify_search_engines_free`) - Free: Free index check: are URLs indexed in Google (`check_if_url_is_indexed`) - Free: Submit a sitemap to Google and Bing (`submit_sitemap`) - Paid: Force indexing: read URL credits and readiness (`get_force_indexing_balance`) - free to call; no purchase or indexing-service call - Paid: Force indexing: quote URLs (backlink and Google indexer) (`quote_force_indexing`) - Paid: Force indexing: submit approved quote (`submit_force_indexing`) - Paid: Force indexing: read job (`get_force_indexing_job`) - Paid: Force indexing: list jobs (`list_force_indexing_jobs`) Example prompts: - "Is https://example.com/new-post indexed in Google? If not, resubmit my sitemap." - "Index these 5 backlinks in Google: quote Force indexing and wait for my approval." - "My pages show 'Crawled – currently not indexed' in Search Console; check them and suggest a fix." Search keywords and tags (most searched first): google indexer, google indexing, page indexer, website indexer, web indexer, indexnow, submit website to google, index checker, google index checker, submit url to google, link indexer, backlink indexer, index backlinks, seo indexer, crawled currently not indexed, discovered currently not indexed, url indexer, google crawl request, indexing service, link indexing service, rapid indexing, request indexing, instant indexing, fast indexing, force indexing, force crawl google Docs: https://docs.crakseo.com/mcp-servers/url-indexing Free URL submission and Force indexing: https://docs.crakseo.com/seo-mcp/managed-indexing
# **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.
Search photos and video moments by visual meaning, people, dates, and folders across local libraries, Apple Photos, and OneDrive. Manage collections, groups, favorites, people, and duplicate review. Synced metadata remains searchable while the desktop is offline; local and Apple Photos media access needs the owning device online with remote access enabled. OneDrive media can be accessed directly from the cloud. OAuth or Bearer API keys. Paid Cloud Access required; hosted visual search uses prepaid credits. Text-in-image search is semantic matching, not guaranteed exact OCR. Setup: https://organizewith.ai/en/guides/connect-ai-assistants
Podcast knowledge for AI agents: search episodes, pull transcripts and ask questions.
Agent car inventory index. Synthetic demo data, not real inventory, not an offer.
Multi-protocol capability index: lookup, live refresh, pay-preflight, endpoint health.
Curated index of 221 AI tools across 21 industries. Search by use case, department or pricing tier.
Google Search Console in your AI: overview, opportunities, index gaps, page checks, long history.
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.
Docs: https://docs.keenable.ai/mcp-server Keenable is a free, remote MCP server that gives agents access to the web index. Search the web with ranked results and date/site filters, then fetch any indexed page as clean markdown. Works out of the box with no account or API key.
AI-readable directory + commerce layer: 3,500+ SEA businesses, plus products from verified stores.
Can I use this URL for RAG, summarize it, train on it or index it? Check observed RSL declarations and machine-readable usage/licensing terms before processing supported content. Use acqpath_capabilities first; acqpath_rights_quote prepares a private quote. Stable HTTP: https://api.getacqpath.com/v1/rights/preflight — no AcqPath account or API key. Fresh 0.02 USDC, deep 0.05 USDC on Base; verified signed offer authoritative. Public payment uses acqpath-request-binding nonce support or the configured AcqPath SIWX adapter for official TS/Python x402 signers. Generic zero-config clients remain unsupported; mainnet paid E2E is unverified. No paid crawl purpose. UNKNOWN is not permission; no license, legal clearance or legal advice. The legacy acqpath_quote routing tool is disabled. Keep private claims outside model context. Integrate: https://developers.getacqpath.com/from-glama
The free AI index for direct booking homes. Any channel, or straight to the host.
Search and read AI summaries of ~3,500 podcast and YouTube episodes.
