"x402 Bazaar MCP (Model Context Protocol) Server" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Financial market context for AI agents, with listed companies' results: www.prereason.com/agents.md
Find the image that explains it: published charts, infographics, screenshots and memes, searchable by meaning, by the words printed inside them, or by visual similarity. Publisher charts (Our World in Data, Eurostat, USDA ERS, EEA) come with source, period and license, and every result carries a ready-to-paste citation. 19 read tools free with no account (daily limits); 2 optional paid tools over x402 or L402.
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Free, read-only Movie MCP Server from FlickDirect. Version 1.5.0 searches movie and TV facts, cast, country-specific dates and ratings when stored, cross-title trivia, quote discovery summaries, soundtrack/player and Additional Songs links, site-wide news and reviews, CinemaCon coverage, eligible stored interview and show transcripts, podcasts, streaming, daily deals and current shop listings. Quote discovery returns availability summaries and source links, never original dialogue or invented paraphrases. Music links retain published affiliate parameters; no track lists or scene placement are inferred. Bounded search recovery, conservative retailer matching and optional fresh retrieval preserve the same two read-only tools and existing inputs. Shop inclusion is not a formal endorsement; retrieval time does not prove upstream currentness. Brief previews and summaries with canonical FlickDirect and published YouTube links only. No full articles, reviews, transcripts or photographs. Free access, no FlickDirect account or API key required. Usage-derived diagnostics expire within seven days; this does not train model weights.
Agentic Finance: 500+ agent tools, multi-chain USDC over x402 or MPP, or free via proof-of-work
Objective Trust ranks MCP endpoints before the caller pays them. Tools: set_objective (free), rank_tools_for_task (API key or $0.005 x402), record_outcome (free). Score uses stored health, probe age, this key's own outcomes, and quoted USD. Sponsored, featured, and click_count are excluded from the score. The caller calls the chosen mcp_url and pays that server. Connect at https://agentshare.dev/mcp/objective-trust.
API discovery and x402 paid execution via MCP. Search by natural-language, call with USDC payment
AiSeek is a global change-intelligence platform that connects AI assistants and autonomous agents to structured, source-linked information about developments across the world. Rather than providing a conventional news feed, AiSeek focuses on identifying meaningful changes, preserving their context, and making the underlying sources accessible. What a source says (fact) is kept apart from what it may mean (hypothesis). Coverage spans artificial intelligence, technology, global economics, financial markets, companies, government policy, science, and other major domains. The MCP server provides sixteen read-only tools. Every name follows one pattern: list_, get_, search_ or verify_. Changes and context: • list_changes — Browse the newest published changes, newest first, 20 per page. • search_changes — Search changes by words in English, Chinese or Japanese, ranked by relevance. • get_change — One change with its sources: outlet, link, date, evidence level and role. • list_topics — Browse curated topics, optionally by coverage domain. • get_topic — One topic and up to 50 of its recent changes. • get_latest_brief — The latest daily or weekly brief. • list_scheduled_events — Upcoming central-bank decisions, data releases, earnings, rule dates and more. Companies: • search_companies — Find a company by name, alias or ticker. • get_company — A company's profile, listings, recent changes, stated facts and relations. Countries and SeekEarth: • list_countries — Every country with its name and this week's number of changes. • get_country_heat — Change Heat per country against its own normal, with a seven-day series. • get_earth_view — One place and moment on SeekEarth: changes, heat and the Earth's layers. Evidence (SeekTrace): • get_change_history — A change's evidence receipts and what AiSeek knew at an earlier time. • get_receipt — One evidence receipt. • verify_receipt — Check that a stored receipt is unchanged. • list_corrections — Public corrections, newest first. Tool calls need an AiSeek API key (Authorization: Bearer or the x-api-key header), made at aiseek.dev/en/account; the handshake and the tool list are open. Optional connection defaults go on the endpoint URL: ?locale=en|zh|ja&limit=1-50&domain=MARKETS. Answers carry sources and links, never quoted passages.
Google keyword search volume, CPC, difficulty, keyword ideas and Google Trends. Pay per call (x402)
Free directory of MCP servers and x402 APIs for AI agents. Find them, or list your own in one call.
Verify AI-generated answers against before anyone acts on them. Oathlayer checks any AI answer, not just legal, and returns a clear tag: Verification Successful, Verification Threshold Not Met, Various Perspectives Apply, Complex Question, or Clarity Needed. Legal citations get their own check: confirmed on official sources, found only on unofficial sites, mismatched with the correct citation shown, or not found. Every check gets a permanent doc number that anyone can verify free at oathlayer.com/verify. One credit per completed check. Works on any AI model.
Web search, page reading, prices and market data for agents via x402, in USDC on Base or Solana.
Search agents and services, and buy Agoreum's checks per call over x402. No account.
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.
Know who you are paying before you pay: Québec contractor and company checks, plus web search. x402.
Find and live-check the paid x402 API for an agent task, ranked by real 30-day payers and price.
Fresh context for agents. Ask, search or follow stories. Each fact cites a Synorb Manifest.
Pay-per-call tools for AI agents, paid in USDC on Base or Solana. Web search, page and PDF reading, crypto news, Hyperliquid perps, market pulse, Chainlink price history, token checks, SEC filings, weather and more. Free calls every day, and a failed call costs nothing. Works with Tollkit Wallet.
The right context at the right time, from the world's leading data providers. One API. 800+ tools.
# **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.
