"ERPNext enterprise resource planning software" matching MCP connectors:
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Emails sent. Purchases made. Code shipped. See what your AI agents did in one private feed. Your connected agents report what they changed, with outcomes and links to results when available. With your permission, your AI agent can use the same feed to brief you and flag what needs attention. Reports come from your connected agents. Actions they do not report will not appear. Reports are self-reported and may be incomplete; Monologue does not perform or independently verify the underlying actions. Browsing, planning, unsent drafts and internal thoughts stay out. Keep passwords, API keys and unrelated private data out of reports.
Send and receive webhooks without building delivery queues or customer webhook controls. Relin lets your software and AI assistants set up inbound handlers, manage outbound events and customer endpoints, inspect delivery health, and retry failed deliveries. A generous free plan is available; no paid subscription is required.
Upfixe is the autonomous PPC engine built for AI agents. With Upfixe's Model Context Protocol (MCP) server, your AI assistant can research keywords, draft responsive search ads, structure ad groups, publish campaigns, and pull cross-network analytics across both Google Ads and Microsoft Advertising (Bing Ads). Features enterprise-grade token encryption (AES-256-GCM) and strict safety guardrails (auto-paused deployments, daily budget caps, O&O syndication filters).
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.
Your agent needs to know how big a website really is — traffic, where it comes from, who else the audience visits, what they pay for ads, and which rivals take the same demand. **What you can ask for** • "How much traffic does this domain get, and how has it trended?" • "Where does that traffic come from — search, referral, social, paid?" • "Who else does this audience visit, and where do we overlap?" • "What keywords send them traffic, and which landing pages receive it?" • "What do they spend on ads, and on which networks?" **How to use it** Point any MCP client at https://mcp.aisa.one/similarweb/mcp and sign in with OAuth — there is no key to create or paste. 23 tools: traffic snapshot, trend and engagement, ranking and top sites, marketing channels and referrals, keywords and landing pages, popular pages and subdomains, demographics, audience interest and overlap, deduplicated audience, ad networks, PPC spend, technologies, similar sites and SERP players. **Why this rather than the source** A competitor's numbers without asking them, and without a seat in an enterprise dashboard. **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 who links to them or who to contact there — 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/sales/mcp to turn the finding into contacts; https://mcp.aisa.one/seo/mcp for the ranking side.
Software for your AI: company files, spreadsheets and rules, with per-person access and history.
Custodio Legal (custodio.legal), software de IA y vigilancia judicial para abogados
# **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.
Governed AI agents for the software your company already runs. 400+ connectors behind one org-wide endpoint, where every call resolves against the current role of the person the agent acts for, not against the connection. Works with Claude, ChatGPT, Cursor, any MCP client, and the Elaichi Agent.
- Brie — Recipe MCP, Meal Plans & GroceriesOAuth unavailableapp.withbrie
Brie connects your assistant to saved recipes, household meal plans and shared grocery lists. Search your recipe library, import recipe links or text, and save a higher-protein or vegetarian adaptation as a named recipe version while preserving the original source. Prepare dinners around your household's preferences, review the proposal, then save the plan and rebuild its groceries. Start with a Brie account on the web and activate your personal Plus or Pro plan, or an eligible trial. Existing subscribers use their current account. Plus starts at $4.99 USD/month, with a seven-day trial for eligible new subscribers; current pricing and renewal terms appear before payment. Household membership alone does not include personal assistant access. Household operations require OAuth and your permission for the selected household. Public discovery exposes tool descriptions only. Eight recipe and grocery tools are available by default; add X-Brie-Capabilities: planning-preview for the thirteen-tool catalog including reviewed meal planning. No private nutrition logs, grocery purchases or billing access. Website: https://withbrie.app Setup: https://withbrie.app/agents Create your account: https://app.withbrie.app/signup?intent=assistant OpenClaw installation: https://clawhub.ai/brie/plugins/brie-openclaw
- mcpOAuthcom.sequentum
Turn the web into structured, reliable, actionable enterprise data for AI Agents
- FinceptOAuthin.fincept
Fincept financial data and analytics: markets, economics, research and terminal tools.
751 Search UK planning applications, entities, datasets, and conservation areas
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.
Load planning for containers, trucks & pallets in Claude & ChatGPT, with a 3D load plan in the chat.
Official remote MCP server for planning personalized trips, discovering destinations, and building itineraries with Sightseer.
- 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
Interactive proposal and pricing-table software for agencies and MSPs. Lets Claude, ChatGPT, or any MCP client create, edit, search, and manage proposals and build reports on your behalf — via scoped, single-org OAuth.
Container load planning in Claude & ChatGPT: what fits, how full, a labelled 3D plan in the chat.
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
