"Overview of HTTP (HyperText Transfer Protocol)" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
Taokeh is accounting software for Malaysian SMEs — double-entry books, LHDN e-Invoice (MyInvois), SST, and full statutory payroll — and this connector opens a company's live books to the AI its owner already uses. 59 tools. The reads answer real questions from the ledger: P&L and balance sheet with server-computed comparisons, cash position, A/R and A/P aging, per-channel marketplace sales, an 8-week cash-flow forecast, tax position, document search with e-Invoice standing, and a one-call daily brief. The writes are drafts only — expenses, invoices, bills, quotes, purchase orders, receipts, credit and debit notes, adjusting journals, bank-statement imports and bank-row suggestions — every figure re-checked by the server, every draft waiting for a human tap in Taokeh. The AI can also work the Shoebox: staff snap paper on free phone logins, and the connector lists the pile, reads each photo, and files the draft with the original attached — the server maps its own stored copy, so the document trail stays byte-perfect. One connection is bound to one company at consent; no tool takes a company argument. Migrating from another system? The same connector stages the chart of accounts, opening balances, contacts, products, historical documents and workspace settings onto the owner's own review screens. Bring your own AI subscription — no per-call fees.
Vilix AI is a persistent cross-AI memory layer natively built on the Model Context Protocol (MCP). Connect once, and your memory, projects, decisions, preferences, and conversation history will follow you across all your favorite, and any other MCP-compatible AI tools: ChatGPT, Claude, Cursor, Codex, Grok, Perplexity, and more. While memory tools solve the problem of switching between apps, Vilix AI also solves the problem of switching between devices: continue your conversation on your phone, then pick it right back up on your laptop minutes later, with full context. Stores actual conversations, not just extracted facts, and has been engineered for long-term storage with years of context rather than days. Exposes get_context (what to say based on relevant memory to recall) and save_turn (what to persist) as core MCP tools, and full project, task, and skill management for agents to track what work is being done. Use cases include ChatGPT memory, Claude memory, Cursor memory, and AI agent memory in a shared layer for founders and developers who are using multiple AI tools and tired of having to re-contextualize everything every single time. OAuth-based setup with no tokens required, including a free tier. See https://vilix.ai/get-started for more information.
Data-ontology maps of your business systems, served to AI agents over MCP.
Persistent memory for AI agents. Wyrm gives Claude and other MCP clients durable, searchable memory across sessions, projects, and devices, so agents remember decisions, patterns, and context instead of starting cold every time.
SEC dilution data, live market data, and news for U.S. equities, with point-in-time as-of queries
DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.
The agentic layer of letters. Agents send real printed mail worldwide, German compliance built in.
Deprecated first registry identity of TrustyCap. Install com.trustycap/trustycap instead.
Read a household’s own book: positions, allocation, AUM, drift, concentration, credit facilities, real assets (property, vessels, aircraft, art) and open compliance breaches. Signs the user in with OAuth 2.1 (PKCE + dynamic client registration), so the assistant holds a scoped token and never a password, and reads that household and nothing else. Every tool is read-only — none can place a trade or move money. Streamable HTTP; official MCP registry ch.antevo/wealth.
Twitter/X, Instagram, Reddit & TikTok data for AI agents. Billions of posts. No API keys.
Real-time web search with answer-ready results for Claude, Cursor and any MCP client. A Tavily alternative: same speed, 20.2% fewer tokens, higher answer quality (60.7% of decided duels won) on a public benchmark. Hosted on mcp.serpdive.com or npx serpdive-mcp.
# Lumethic Photo Verification Lumethic checks whether a photo is a real, unmodified camera capture. Give it the RAW file and the JPEG export from the same shot and it compares the two with forensic algorithms, or hand it a single image and it validates the C2PA Content Credentials embedded by the camera or editing software. The result is an authenticity verdict with confidence, per-check findings, and a shareable report. This remote MCP server puts the whole workflow inside your assistant: verify photos, organise them with tags and private comments, share reports, and publish verified work to a public portfolio page with an evidence-backed badge. **Endpoint:** `https://api.lumethic.com/mcp` (Streamable HTTP, OAuth 2.1) ## Connect Sign in from the assistant. The first connection opens a Lumethic consent screen; enter your email and the six-digit code we send, choose what the assistant may do, and you are connected. New addresses get a free account. Claude Code: claude mcp add --transport http lumethic https://api.lumethic.com/mcp Claude.ai and Claude Desktop: Settings → Connectors → Add custom connector → paste the endpoint URL. Servers, scripts and CI can use an API key instead, sent as `Authorization: Bearer ask_…` or `X-API-Key: ask_…`. Create one at https://www.lumethic.com/en/profile. ## Tools Verify - `verify_photo` — verify a RAW + JPEG pair; inline base64 for small files or object keys from `create_verification_upload` for large ones. Uses quota. - `verify_content_credentials` — validate a single image's C2PA Content Credentials and run advisory forensic screening. No RAW needed, free. - `create_verification_upload` — pre-signed upload URLs for large RAW files. - `get_verification` — status, verdict, per-check results and the evidence report; poll until `completed`. - `list_verifications` — your verifications, filterable by status, result and tags. Organise - `list_tags`, `set_verification_tags`, `add_verification_tags`, `remove_verification_tag`, `update_tag`, `delete_tag` — tag verifications and manage the tag vocabulary by name or id. - `list_verification_comments`, `add_verification_comment`, `update_verification_comment`, `delete_verification_comment` — private notes on a verification, visible to your account only. Share and export - `share_verification`, `get_verification_share`, `unshare_verification` — create a public or invite-only report link, read it, or revoke it. - `request_psd_export`, `get_psd_export_status` — a layered flicker-comparison PSD (original, registered RAW rendition, SSIM heatmap) for Photoshop. Verified Portfolio - `get_portfolio`, `create_portfolio`, `update_portfolio`, `delete_portfolio` — your public portfolio page: slug, display name, tagline, website, publish state. Paid plans. - `add_portfolio_item`, `update_portfolio_item`, `reorder_portfolio_items`, `remove_portfolio_item` — curate up to 50 verified photos with titles and order. Adding a photo makes its report publicly viewable; the assistant is told to confirm with you first. Account and marketplace - `get_account_usage` — plan, verifications used and remaining this month. - `get_upgrade_link` — a sign-in link to the upgrade page when quota runs out. - `get_listing`, `list_my_listings` — your Lumethic marketplace listings. Resource: `lumethic://pricing` describes plans, monthly limits and authentication options. Every tool carries MCP annotations: reads are read-only, publishing and sharing tools are marked open-world, and irreversible actions (unsharing, deleting, editing a comment) are marked destructive, so assistants can ask before acting. ## Scopes Choose on the consent screen what the assistant may do: `verifications:read`, `verifications:write`, `shares:write`, `portfolio:write`, `listings:read`, `account:read`, `offline_access`. Review and disconnect assistants any time from your Lumethic profile. ## Pricing The Free plan includes 5 RAW+JPEG verifications per month; Content Credentials checks are free and unlimited. Paid plans raise the limit and unlock the Verified Portfolio and PSD exports. https://www.lumethic.com/en/pricing ## Links - Documentation: https://www.lumethic.com/en/mcp - REST API: https://www.lumethic.com/en/api - Privacy policy: https://www.lumethic.com/en/privacy-policy - Terms: https://www.lumethic.com/en/terms-and-conditions
IPStack MCP Adapter turns IPStack's REST APIs into Model Context Protocol tools so any MCP-compatible client can call them directly in conversation. The first release ships IPStack IP geolocation and security lookups (single IP, caller's IP, and bulk). Additional APILayer services are added by registering them in a single config file, so the catalog grows without client-side changes.
Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.
Real-time US business entity search across all 53 US jurisdictions - all 50 states, DC, Puerto Rico, and US Virgin Islands. Search, verify, and check the status of any LLC, corporation, or registered entity. Ideal for KYB, due diligence, and vendor verification.
AXL MCP lets AI assistants create and manage landing pages, courses, email campaigns, CRM records, and marketing workflows inside AXL. Built for growing expert businesses, it turns chat requests into real work across sales, marketing, and course delivery. An AXL account is required. Sign in securely with OAuth 2.1. Website: https://axl.tech/developers/mcp . Setup guide: https://docs.axl.tech/mcp . Watch AXL in 77 seconds: pages, courses, CRM, and automation. Product overview: https://www.youtube.com/watch?v=jlhR9CafIww
Search and share firsthand reviews of products, APIs, services, places, and organizations.
The vetted, cross-LLM marketplace of doer agents — itself an MCP server.
Millions of dated buying and momentum signals: who raised, who's hiring, what changed and when
# **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.
