"Information about PostgreSQL database management system" matching MCP connectors:
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Ask about your taxapp.nz records and NZ tax; adds records only if an owner allows. Sign-in required.
Project portfolio management for PMOs. Alternative to Microsoft Project Online. OAuth + PAT.
Connect your AI assistant to your Peec AI account to monitor and analyze your brand's visibility across AI search engines like ChatGPT, Perplexity, and Gemini. Ask questions about brand visibility, competitor comparisons, source citations, and trends: all in plain language, directly from your AI tools.
Read-only access to business data from Exact Online, Twinfield, AFAS, Nmbrs, Moneybird, HubSpot and 30+ other sources for ChatGPT, Claude and other MCP clients. DigiData syncs each source into a dedicated PostgreSQL database per customer; the MCP server exposes bounded tools (list_sources, list_tables, describe_table, query_table, aggregate_table, get_sync_status) over admin-approved tables and columns only. OAuth 2.1, no write tools, no arbitrary SQL.
# **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.
French B2B database for companies and contacts, from official French registers (INSEE, Infogreffe, BODACC) and public web sources. Search, count, fetch entities and export a small CSV from Claude or any MCP client. OAuth with a Basile account; API-access plan required. France only.
Nephia is a brand monitoring service, and this is its remote MCP server. Claude, Cursor, ChatGPT or any MCP client can read the mentions your brand gets on 14 sources: X, Reddit (posts and comments), YouTube, TikTok, Bluesky, Hacker News, Mastodon, Lemmy, GitHub, Product Hunt, Stack Overflow, any RSS feed, Vinted, and AI answers from ChatGPT, Gemini and Perplexity. Every mention arrives already read, with its sentiment and intent, so an agent can answer plain questions: which complaints came in since Friday, what Reddit said about us this week. The source is an argument, not a tool, so one call reads every source you watch. Sign-in is OAuth in the browser: no API key to copy. The consent screen has three permissions: read your mentions and Queries, change what is running (pause, resume, retire), and spend credits (semantic search and AI passes), which arrives unticked. Every tool description states its cost, so a model can budget before it spends. The server is on every plan, Free included, and reading your own mentions through it costs nothing.
Farm management for Brazilian farms: pest scouting, rainfall, work orders, inventory, fleet, post-harvest and cost per field. Reads and records, with OAuth on the user's own upCampo account. Nothing is ever deleted.
Connects Amazon Seller Central and Amazon Advertising to any MCP client. Settlement-accurate P&L - every fee, refund and reimbursement as Amazon posted it - plus contribution margin and breakeven per product, per marketplace, per day. Full Sponsored Products, Brands and Display management: search terms, placements, keyword and competitor research, dayparting, automation rules. 110 tools: 78 read-only (P&L, PPC at every grain, SQP/Brand Analytics, inventory, forecasting), 28 staged writes (every change is a proposal you review and confirm before it reaches Amazon - there is no autonomous-write mode), and 4 confirmation & support tools. 4 additional AI Workforce tools appear once a client is connected.
Digital asset management platform with AI-powered file search, semantic similarity, workspace management, folder trees, notes, and persistent memory. 59 tools. Connect with your Razuna access token.
Zero-value tracer token system that tracks AI agent activity across the internet. Agents earn tokens by submitting threat intelligence traces, with free trust verification (verify_trust) and paid threat intelligence feeds. 8 tools: submit_trace, check_token_balance, mutate_token, get_trace_schema, verify_trust (free) + threat_intelligence_feed, bulk_verify_trust, query_trace_analytics (paid).
Hosted long-term memory for AI agents via MCP. Recalld updates facts as information changes and retrieves relevant context. Connect with a Recalld US account.
Connect AI agents to BoomTax for IRS information return filing. Query filings (1099, W-2, 1095, etc.), check e-file status and errors, look up payers, and get filing summaries across tax years. **Tools:** - Search and filter filings by tax year, form type, and status - Get filing details with payer info and e-file status - View e-file errors with IRS error codes and messages - Look up payers/issuers with filing counts - List all supported filing types and e-file availability
Model Context Protocol (MCP) server for FinGo: construction budget lookup, official Caixa/IBGE SINAPI database for all 27 Brazilian states, and construction financial
Remote MCP server implementing the Streamable HTTP transport with 25 tools for AI assistants. Enables programmatic management of multi-platform content publishing — create posts, run automations, manage RSS feeds, generate hashtags, search images, and publish to 13+ platforms (Instagram, LinkedIn, X, WordPress, etc.). Authenticated via Bearer token.
Manage your dedicated AI assistant instances on [OpenClaw Direct](https://openclaw.com) through natural language. Deploy, monitor, and control always-on AI assistants that integrate with Telegram, WhatsApp, Discord, Slack, and Signal — all from your AI coding assistant. Learn more about the [MCP integration](https://openclaw.com/openclaw-mcp-integration).
Project management, CRM, time tracking and project economy for consulting and engineering firms
Posty is a social media management MCP server for creating, scheduling, reviewing, and managing content across multiple social channels and workspaces. It lets AI assistants discover connected accounts, create and edit posts, schedule publishing, submit content for approval, approve or reject posts, add comments, and view upcoming scheduled content. Built for teams, agencies, and creators, Posty makes it possible to manage real social media workflows directly from MCP-compatible AI clients.
Most AI still formulates skincare with 1940s HLB logic: pick emulsifiers, balance a number, heat two phases, homogenize and hope it holds. TDA (Tri-Domain Architecture) logic is the new standard. Nanocolloidal, liposomal and nanomicellar domains coexist in one chassis, held stable by electrostatic (DLVO) design, so the formula is the delivery system. NanoBase™ is the Architecture TDA logic is built on, and this server teaches your AI assistant to formulate with it. Build modern nanocosmetics, cold: - No heating, no hot oil and water phases, no high-shear homogenizer. Actives go in at room temperature with gentle mixing, which also spares heat-sensitive actives. - No specialized nano equipment. A scale, beakers, an overhead mixer and a pH meter are enough. - No emulsifier blends to source, weigh or balance. The Architecture replaces them. - Every finished formula is a true nanoformulation: on average about 250 nm, a quarter of a micron, measured by DLS. What your AI can do: - Learn TDA logic: how ingredients route into the three domains, and why. - Search more than 2,000 cosmetic ingredients by INCI name, with published third-party delivery data for actives at the nanoscale, with citations. - Check a finished formula against the NanoBase™ loading envelope: verdict, remedies, maximum loads and the pH window (5.7 to 6.2). - Check preservation against regulatory caps. - Build the on-pack INCI label or an internal composition sheet. - Add ingredients the library lacks: upload the supplier document and it is added for you and every user after you. Privacy: formulas are discarded after each answer and conversations are never received. Supplier documents for unlisted ingredients are kept, without the formula or your identity in clear, to grow the library. For brands, independent formulators, labs and contract manufacturers. Outputs are design guidance for leave-on cosmetics and should be reviewed by a qualified chemist or formulator. Free plan at nanobaselabs.com/api.
Beamline UI installs React UI code into your own repository: 250+ components and 50+ complete screens by Danylo Pravda. Editable source lands in src/ui/beamline; compiled archives live in your app's .beamline/packages/. Commit those files with your app. Nothing at runtime calls Beamline servers. The hosted MCP server is an optional discovery and installation tool for your coding agent; the shadcn CLI installs the same parts. Nine looks, dark and light. The Complete System is $49 launch price, plus VAT or sales tax where it applies: one payment for one person's Beamline account, MCP, library, installs and updates, with lifetime updates for as long as we publish the purchased system. Teammates, contractors and clients may use, edit, build and ship the installed code as part of that app. They need their own licence for Beamline access or to take its parts into other apps. The free sample remains MIT, including commercial use. https://beamline.io
