"Development-related MCP resources" matching MCP connectors:
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Generate synthetic random user data for testing, demos, and development without using real persona.
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/
Search, read and save your Linko notes and resources (AI knowledge base) from any AI chat.
# **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.
Traceable is a document-style workspace that keeps your design records connected and visible. It replaces spreadsheets, wikis and disconnected tools with one place to author, trace, control, review and publish the documentation your standards demand, with live traceability, gated e-signatures and audit-ready output. Manage your source of truth for any product development, especially regulated products such as medical device, SaMD, IVD and Defence.
Spec-driven development for AI coding agents: live requirements, stories and traceability over MCP
AgentPMT is the AI agent marketplace that turns any MCP-compatible AI assistant into an autonomous employee. Connect once and your agents gain access to a growing ecosystem of tools, workflows, and skills spanning communication, data analytics, development, file management, search, and more. AgentPMT dynamically discovers and orchestrates tools from across the MCP ecosystem, so your agents can independently find the right tool for any task without manual configuration.
Your agent needs to crawl a site and say what is wrong with it — broken tags, duplicate content, pages nothing can index, resources that never load. **What you can ask for** • "Crawl this site and list every page with a duplicate title or missing description." • "Which pages are non-indexable, and why?" • "Run Lighthouse on these URLs and give me the failing audits." • "Show the internal link graph and the orphan pages." • "Give me this page's raw HTML and its microdata." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-onpage/mcp and sign in with OAuth — there is no key to create or paste. 20 tools: submit a crawl and read its summary, pages, resources, links and waterfall; duplicate content and duplicate tags; keyword density; non-indexable and uncrawlable resources; parsed content, raw HTML, microdata, screenshots and Lighthouse. **Why this rather than the source** A crawler you drive from the agent, with the audit results as structured data rather than a PDF. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Find the broken pages here, then ask the same agent what those pages used to rank for — 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/mcp for all of it at once — rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
Your agent needs the derived numbers — domain authority, what a site ranks for, related and relevant keywords, search intent, and who the real competitors are — for Google, Amazon and the app stores. **What you can ask for** • "What is this domain's authority, and how has its rank history moved?" • "Which keywords does this site rank for, and with what intent?" • "Who are this domain's organic competitors, and where do we overlap?" • "Which keywords does this Amazon product rank for?" • "Compare these two domains keyword by keyword." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-labs/mcp and sign in with OAuth — there is no key to create or paste. 46 tools: ranked, related and relevant keywords, keyword ideas and intent, domain authority and rank history, competitor and intersection analysis, bulk metrics, plus the same shapes for Amazon products and Apple and Google Play apps. **Why this rather than the source** Ahrefs domain rating, Semrush rank history and DataForSEO Labs answering the same questions side by side. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Size the competitor here, then ask the same agent for their traffic mix or their contacts — 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/mcp for all of it at once — rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
Bareun (바른) is a Korean natural-language engine. This MCP server lets any MCP-compatible client hand Korean text to a dedicated Korean engine instead of guessing: analyze_syntax (morphological analysis with 47 POS tags and beta homograph sense disambiguation), analyze_syntax_raw (raw model output, no post-processing), tokenize, correct_grammar (spelling and spacing correction with per-edit blocks and rule categories), and list_pos_tags. Resources expose the POS tag table, server info, and the cu
PGA's official MCP Server for all things golf-related. Find a coach, play golf, improve your game.
Remote MCP server exposing SMI Aware tools, resources, and skills over Streamable HTTP.
Toolstile is a managed MCP gateway that connects remote MCP servers behind one endpoint, with per-agent permissions, shared accounts and activity logs. Connect at https://mcp.toolstile.com/mcp over Streamable HTTP with OAuth; sign in at https://toolstile.com, select a workspace and connect your upstream servers. Available tools, resources and prompts depend on that workspace and the agent's granted access.
Hubris is an OpenAI-compatible LLM gateway for the Russian market, billed in rubles. This MCP server gives agents access to the model catalog (400+ models with ruble pricing), account balance, and chat completions with full parity to POST /v1/chat/completions. Tools: models_list, models_search (filter by capability/price/context length), models_get_pricing, balance_get, chat_complete. Resources: hubris://catalog/models, hubris://docs/quickstart. Prompt: compare-models. Docs: https://hubris.pw/
- MySpecOAuthdev.myspec.mcp
Interactive AI architect for Spec-Driven Development (SDD). Interviews developers and manages structured 4-file spec bundles (constitution.md, requirements.md, solution.md, tasks.md) with 31 tools for Cursor, Claude Code, and Windsurf.
Recallium is an MCP server that gives development agents a shared, persistent memory of your engineering work. Decisions, root causes, fixes, constraints and team rules worked out in one session are found and handed to every engineer and agent on the project in the next, across Claude Code, Codex, Cursor, GitHub Copilot and 60+ MCP clients. One install connects every agent on the machine.
Pinterest keyword research from our own crawl: saves, competition, related terms, trends, top pins.
Live and historical Polymarket prediction-market orderbook data — plus Hyperliquid perpetual-futures orderbooks — for any MCP-capable AI agent. 12 tools and 2 resources covering market discovery, live order books, time-series snapshots, multi-day summaries, and pipeline health. Tier-aware: the same endpoint serves free (BTC, 24h history) through Enterprise (all categories, unlimited history) automatically based on the API key.
Google Trends: interest over time, by region and city, related and rising queries, and Trending Now in any country. Compare keywords on one scale. Runs on Apify, $1 per 1,000 keyword reports.
- ZopnightOAuthdev.zop.api
Read-only cloud cost and infrastructure governance across AWS, Azure and GCP. 85 tools covering cost overview and trends, cost by provider/resource/tag/team, budgets, resources, schedules, recommendations, tagging policies, audit logs, anomalies, Kubernetes resources and pod logs. Hosted remote server, nothing to install. Docs: https://zop.dev/learn/mcp-server?utm_source=glama&utm_medium=listing&utm_campaign=mcp-directory Claude setup: https://zop.dev/learn/how-to/set-up-zopnight-mcp-for-claude
