"Understanding Code Execution" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
MCP server for the EmblemAI AgentWallet. Exposes tools for token swaps, DeFi yield farming, liquidity management, portfolio tracking, market research, and memecoin discovery across Solana, Ethereum, Base, BSC, Polygon, Hedera, and Bitcoin. Backed by Agent Hustle (agenthustle.ai) for routing and execution. OAuth 2.0 + PKCE for interactive agents; API key and x402 micropayments also supported.
The official MCP Server for the Mux API
Search public open-source code, documentation, metadata, vulnerabilities, changelogs, and examples.
Compliance frameworks delivered to AI agents. Nizh gives your agent read access to your organization's compliance program — SOC 2, ISO 27001, CMMC 2.0, NIST, and more — as MCP tools, so it can check posture, read a control's objectives before changing code, and record where evidence lives.
Connect Claude, Cursor or any MCP client to AppSigma and let your AI research apps, read reviews and track rankings on its own – no glue code.
# **RChilli MCP Hub** RChilli MCP Hub is a production-grade MCP server that exposes RChilli's full HR data intelligence platform as 17 AI-callable tools across 4 categories. Built on 15+ years of HR data intelligence, it is trusted by ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. Every tool is read-only and returns a consistent, structured JSON response — no raw exceptions, no inconsistent formats. <br> --- <br> # **Tools — 17 Total** userkey and subuserid are injected automatically from your Bearer token — you never need to pass them manually. <br> --- <br> # **🔍 Resume & Job Description Parsing — 3 tools** <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. When used on a careers page or application form, the same extraction call auto-fills every application field in under 10 seconds — documented to increase candidate conversion by up to 194%. Supports 40+ languages with English-normalized output for global intake, and runs in batch mode to process legacy databases or migration backlogs overnight at scale. Also supports resume reprocessing — re-running previously extracted resumes through the latest extraction logic and taxonomy version to bring older records up to current data quality, without requiring a new document from the candidate. Distinct from bulk import (first-time extraction of a new batch) and from talent data refresh (re-enrichment from a newer submitted resume). <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 the Resume Data Extraction tool. Ideal for pipeline automation where resumes are stored in cloud storage, S3, or email attachments. Also supports the same auto-fill, multilingual, and batch-processing capabilities as the core extraction tool for URL-based intake sources. <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 for recruitment automation and candidate matching. <br> --- <br> # **🧠 Skills & Job Taxonomy — 4 tools** <br> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, all aliases, related skills, proficiency levels, and O*NET/ESCO mappings. Use when you need the complete record rather than a ranked search. <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> > ### **`autocomplete_skill`** > > Accepts a partial skill string (min 2 chars) and returns up to 10 ranked autocomplete suggestions with canonical names and categories. Prevents free-text entry errors and keeps skill data clean at point of entry. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title string and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to taxonomy profiles from the moment a recruiter starts typing. <br> --- <br> # **🛡️ Redaction, Documents & Utilities — 7 tools** <br> > ### **`redact_resume`** > > Redacts personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. Configurable redaction scope. Idempotent. <br> > ### **`reformat_resume_with_template`** > > RChilli's Resume Reformatting tool accepts any structured candidate profile and applies one of six branded templates (TM001–TM006) to produce a consistently formatted output document in PDF, DOCX, RTF, or HTML — ensuring every candidate is presented in a standardized, professional layout regardless of how their original resume was structured. Designed for staffing firms, recruitment agencies, and enterprise HR teams who need to control candidate presentation at scale, it eliminates manual reformatting effort and enforces brand consistency across all submissions. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Preserves formatting fidelity. Useful as a pre-processing step before data extraction on non-standard file types. <br> > ### **`tag_entities`** > > RChilli's Named Entity Recognition tool takes already-extracted HR text and annotates it by wrapping each recognized entity in a structured XML-style label inline — returning output such as `<job_title>Senior Data Engineer</job_title>`, `<skill>Python</skill>`, `<city>Austin</city>`, `<degree>Bachelor of Science</degree>`, and `<organization>Google</organization>` — covering 10+ HR-specific entity types including person name, state, country, date, and year. Unlike data extraction tools that produce separate field lists, tag_entities preserves the full original text structure with entities labeled in place, making the output immediately consumable by ATS field-mapping pipelines, candidate profile builders, and content annotation workflows without any offset calculation or post-processing. <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. Safe for GDPR/CCPA workflows. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Enables radius-based candidate and job search and supports workforce planning analytics. <br> > ### **`classify_job_zone`** > > RChilli's Job Zone Classification tool reads the job profile from a resume or job description and returns its O/*NET Job Zone — one of five standardized levels ranging from Zone 1 (little or no preparation required) through Zone 2 (some preparation), Zone 3 (medium preparation), Zone 4 (considerable preparation), to Zone 5 (extensive preparation required) — based on the education, experience, and training criteria defined by O/*NET. The returned Job Zone level enables downstream workflows such as candidate-to-role fit filtering, compensation benchmarking, over/under-qualification flagging, and job architecture standardization without any manual O/*NET lookup. <br> --- <br> # **🎯 Search & Matching — 3 tools** <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one Job Description (no index required) and returns an overall match score, dimension scores, skill gap list, and natural-language explanation. Bias-controlled and audit-ready. <br> > ### **`find_matches_in_index`** > > Accepts a resume or Job Description as input and returns the top-N most similar documents from the indexed corpus ranked by semantic similarity. No index setup required for the input document. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant's pre-populated index. Supports Boolean and semantic search modes. Requires documents to be indexed before use.
- aicutOAuthpro.aicut.mcp
Generate AI videos and images from Claude, Claude Code . Browse the curated model catalog with per combination pricing, price a job before spending, generate, and pull finished assets from your aicut library.
MCP connector for PPC teams using AI agents to launch landing pages and improve post-click performance. Build landing pages, import existing code, run A/B tests, track conversions, manage domains and branding, and view CRO reports in UXON AI.
- FalconerOAuthcom.falconer
Give your agents trusted access to a company's living documentation. Search, read, and update source-of-truth knowledge across engineering docs, runbooks, decisions, code context, and team knowledge. `https://falconer.com/mcp
- reapOAuthvideo.reap.mcp
The Reap MCP server connects your AI agent directly to your Reap workspace. Once connected, your agent can run the full pipeline for you — upload a video, generate clips, add captions, reframe, dub, transcribe, and publish to social platforms — all from inside your chat. Works with Cursor, Claude Code, VS Code, GitHub Copilot, Codex, Gemini CLI, and any other MCP-compatible agent.
Regulatory data API for global product compliance. Returns substance limits (CosIng, REACH, FDA, Prop 65), HS code classification, duty rates, and sanctions screening across 131 countries.
Create on-brand marketing deliverables and GTM documents using customizable blueprints with centralized company context and brand guidelines. Organize content production into projects while leveraging community-vetted templates to accelerate go-to-market strategies. Export finalized materials directly to Microsoft Word or share them directly with a link to external stakeholders.
Give ears to Claude/Openclaw/Hermes/Codex/Grok Bot. Voibe turns recordings into text your AI agent can work with. Ask your agent to transcribe a meeting, interview, call, lecture, podcast episode or voice memo. The raw transcript arrives in the chat with speaker labels, timestamps and a summary. Attach the file in the chat, or point at a file or folder in Claude Code, where a whole folder of recordings works in
DataGrout is an enterprise MCP gateway that connects AI agents to Salesforce (700+ tools), QuickBooks Online (550+ tools), Oracle Fusion Cloud (1,000+ tools), and any MCP-compatible system through a single endpoint. Semantic tool discovery surfaces the right tools from plain language goals without flooding the agent context with hundreds of schemas. Every workflow is verified with a Cognitive Trust Certificate before execution. Warden scans every tool output for prompt injection before it reache
Connect Floniks to any MCP client — Claude.ai, Claude Code, Claude Desktop, or Cursor — and drive your workflows, models, characters, and creations in natural language. Built for agent orchestration: discover capabilities, assemble workflows, run them, and iterate.
- aictrlOAuthdev.aictrl
Governance and grounding layer for engineering teams running AI coding agents (Claude Code, Cursor, Codex). Grounds agents in your codebase's knowledge graph, and adds session audit, policy controls and cost/token visibility.
An accounting engine your AI connects to over MCP. Hand it bank and card statements, invoices, bills and receipts; get reconciled double-entry books with every number traceable to the page it came from. Requires a host that can reach files on your machine — Claude Code, Codex, Cursor, Grok Build, or Claude Desktop + Cowork. Browser chat can install it but cannot send files. Open beta; first 1,000,000 tokens free.
- PuterOAuthcom.puter.mcp
Puter MCP lets your AI tools (Claude Code, Codex, or any other MCP-compatible client) interact with your Puter resources: managing files, publishing websites, deploying workers, and more.
Search people, companies, posts, and jobs across LinkedIn and Sales Navigator using natural language — no code, no workflows, structured data output, built by Periodix (4.9/5 on G2).
Premium low cost execution layer for AI trading agents, with access to perpetual futures trading across 500+ pairs and $10B+ in aggregated liquidity. Built for low fee, token efficient agent execution with a 0.035% taker fee.
