"Development-related MCP resources" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
NSW DAs, CDCs and property planning reports: zoning, height, FSR, nearby DAs. Pay per call via x402.
VAREXIS-INDEX — Source-Linked Evidence & Verification Tools for AI Agents VAREXIS-INDEX provides free, source-linked evidence for agent decisions through six focused guides and two distinct read-only MCP connectors. The original `/mcp` connector covers the approved search and preview population. The companion `/mcp/catalogue` provides deterministic access to 355 additional records by category and exact identifier. Configure both through the existing quickstart: https://varexis.tech/index-connect#quickstart Four optional one-time local checkers analyse supported customer-supplied declarations: Tool Admission £49, Audit Coverage £79, Data Exit £79 and Transaction Integrity £149, excluding VAT. These products do not independently inspect live systems, enforce permissions, establish payment settlement, verify deletion or certify compliance. Six free decision guides: https://varexis.tech/index-packs#free-decision-guides Evaluate agent permissions, delegated authority, audit provenance, payment integrity, data retention and software supply-chain evidence before relying on documented claims. **FREE MCP CONNECTOR** Endpoint: https://varexis.tech/mcp Connect using Streamable HTTP. No authentication is required for public evidence discovery. Four free, read-only tools: - find_evidence_questions — Find existing reviewed evidence questions and matching routes. - preview_evidence_answer — Retrieve complete supported public answers, sources, limitations and snapshot hashes. - find_package_advisories — Find source-bound software advisory records. - get_index_access_options — Discover available services, pricing, licensing and purchasing requirements. Public MCP cannot execute actions, inspect private systems or authorise deployment. Developer quickstart: https://varexis.tech/index-connect **LICENSED VERIFICATION TOOLS** Four separately licensed, reusable local executables: **1. Agent Tool Admission & Permission Control — £49** Compare declared tool actions, resources, recipients and permissions across supported GitHub, Playwright, Notion and Slack integrations. Identify authority conflicts, missing verification and permission changes before human review. **2. Agent Audit & Evidence Coverage — £79** Reconcile declared identities, authorisations, actions and outcomes. Identify missing audit events, inconsistent references and unresolved export, retention or recovery evidence. **3. Agent Data Exit & Retention Reconciler — £79** Compare declared data inventories, exports, deletions, retention conditions and residual copies. Identify missing evidence and unresolved data-custody conditions during migrations and offboarding. **4. Agent Transaction Integrity & Replay Analyzer — £149** Reconcile declared spending authority, amended transaction terms, scoped idempotency keys, retries and reported outcomes. Identify conflicting purchase attempts and unresolved payment or entitlement evidence. All four products are separately licensed for reusable internal execution. Prices are one-time, exclude applicable VAT and do not include subscriptions, hosting or future updates. Checkers analyse supplied declarations locally. They do not independently inspect production systems, execute payments, enforce permissions, certify compliance or establish financial settlement. Explore all products, representative findings and free previews: https://varexis.tech/index-packs **FREE EVIDENCE PACKS** Seven complete public evidence packs cover: - GitHub and Playwright permission boundaries. - Notion and Slack access and data handling. - Audit and export evidence coverage. - Next.js advisory source assertions. - SonarQube, Snyk and Semgrep scanner trust. - Telemetry redaction and exception handling. - GitHub release approval and artifact identity. Source reviews include documented versions, provenance, exclusions and reliance boundaries. They are not independent deployment tests or current security certifications. 355 additional reviewed records are publicly available through exact-ID HTTP catalogue links and the separate read-only https://varexis.tech/mcp/catalogue connector. They remain outside the original MCP search and preview population and paid saved retrieval. Enhanced natural-language search for these additions remains on HOLD. Public catalogue: https://varexis.tech/varexis-index.json **SAVED EVIDENCE & SUBSCRIPTIONS** - Single Request: £5 — Save a version-bound published evidence result or obtain the eligible original Agent Tool Evaluation & Integration Kit. - Evidence Receipt: £19 — Add an unsigned delivery receipt to the eligible saved result. - Research: £29/month. - Developer/API: £149/month. Prices exclude applicable VAT. Subscription eligibility, rate limits and exclusions apply. The four separately licensed verification executables are not included in these existing evidence or subscription offers. **AGENT PURCHASING & RECOVERY** VAREXIS supports hosted Stripe checkout and compatible authorised MPP/Stripe Shared Payment Token purchasing through separate payment interfaces. Agent purchases require owner spending authority for the exact VAT-inclusive quote and any necessary provider authentication. Not every agent or wallet is supported. Public MCP remains free and read-only. Payment credentials and private customer data must not be submitted to the public connector. Existing purchases should be retrieved using the original credential. Uncertain payments must be investigated and recovered through supported procedures, not automatically purchased again. Purchase or recover: https://varexis.tech/index-access Agent payment contract: https://varexis.tech/varexis-index/agent-payments.json **WHY VAREXIS?** VAREXIS combines source-linked evidence, explicit limitations, versioned deliverables and structured verification of supplied declarations. Its purpose is to help agents and developers distinguish what available evidence actually establishes from what remains uncertain, unsupported or outside authority. Free evidence discovery. Transparent product scope. Reusable local verification. Bounded reliance. Website: https://varexis.tech Developer integration: https://varexis.tech/index-connect MCP endpoint: https://varexis.tech/mcp
Find local businesses across Cape Town, the Winelands and the rest of the Western Cape. Search by service or name, see menus and price lists in rand, then start a booking, quote or order in WRDO.
x402 layer for AI agents: 35 pay-per-call resources, x402 service discovery, USDG/USDC.
Generate synthetic random user data for testing, demos, and development without using real persona.
Free read-only check of a public GitHub repo for eight security signals related to the EU CRA.
Read Schedule it events, resources, groups and labels; create and update events and resources.
Google Trends interest over time, by region, and related queries and topics, as JSON.
Search the FAA handbooks, advisory circulars and Airman Certification Standards (ACS) used for pilot training, and read any page in full with its figures, charts and tables. Every result links back to the exact page so answers can be cited. Free, public, no API key.
MCP server for LingoHub — localization projects, resources, exports and repository pushes.
Your job is to win new business, not to spend hours researching medical device companies. Whimbrel saves you hours of research inside the AI app you already use. Whimbrel is for sales and business development teams at firms that sell to medical device companies: contract manufacturing, sterilization, testing, design, regulatory and software services. Every fact links to its public source. Your first month is free. https://whimbrelresearch.com/
Your job is to win new business, not to spend hours researching medical device companies. Whimbrel saves you hours of research inside the AI app you already use. Whimbrel is for sales and business development teams at firms that sell to medical device companies: contract manufacturing, sterilization, testing, design, regulatory and software services. Every fact links to its public source. Your first month is free. https://whimbrelresearch.com/
Review Cliento locations, staff, resources, services, products and stock.
Read Hub Planner resources, projects, bookings and timesheets; create clients and time entries.
MCP server with non-medical guidance for patients and families living with MS, Parkinson's, or Alzheimer's. 48 guides and 212 curated resources across communication, care logistics, grief, and planning. No auth required.
Search, read and save your Linko notes and resources (AI knowledge base) from any AI chat.
Free deterministic security scan of public git repos: OSV.dev vulnerable deps, secrets, config lint.
# **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.
Live MCP connector for Develust Technology's services — web development, infrastructure, backend architecture. Hybrid search with AI reranking for accurate results. No auth required.
Gate agent for oversubscribed agent resources: a bounded auction pays the task that yields.
