"Code Execution" matching MCP connectors:
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A fast first-pass screen against the USPTO federal register — sound-alikes, look-alikes, and same or related classes, in plain English. Below are all Tool descriptions 1. screen_trademark Screen a brand name against the USPTO federal register. Read-only. Use this FIRST for any name. Returns JSON with a plain-English risk verdict (HIGH / MEDIUM-HIGH / MEDIUM / LOW), ranked conflicting marks (each with sound/appearance similarity, class relatedness, live/dead status, owner, serial), and the data-as-of date. Pass format "csv" to get the same results as a spreadsheet (one row per hit) instead of JSON. Limited to 100 screens/day on this server. SCREEN ONLY — not a clearance opinion, not legal advice. After this, use check_global_marks for EU/UK, check_domains for the domain, and watch_mark to monitor the name. 2. trademark_status Authoritative status for ONE mark you already know, by serial number (sn12345678) or registration number (rn1234567). Read-only. Returns JSON with the mark's live/dead status, owner, classes, goods/services, and filing/registration dates. Uses TSDR if a free key is set, otherwise the public Trademark Search record. Use when you have a serial/registration number (e.g. from a screen_trademark hit) and want the authoritative record for that one mark — not for searching by name (use screen_trademark for that). 3. suggest_classes Suggest the Nice classes (1-45) a goods/services description falls under, with reasons. Read-only, pure reasoning — no live data, no register lookup. Input goodsDescription is what you sell (e.g. 'music streaming app'); the more specific it is, the better the classes. Returns JSON with the suggested classes (each with its label), the classes assumed from your wording, and the reasons. Use before filing to pick classes (each class costs $350 to file), or to feed classes into screen_trademark / check_global_marks. Always verify against the USPTO ID Manual for the exact pre-approved description. 4. analyze_name Analyze a brand name's strength WITHOUT checking the register — read-only, offline, deterministic (same name always gives the same result). Returns JSON with the distinctiveness spectrum (fanciful / arbitrary / suggestive / descriptive / generic), phonetic collisions to check, and a checklist (other-language meanings, common-law use, state registers). Optional goodsDescription (what you sell) sharpens the analysis: a descriptive word for those goods scores weaker than the same word for unrelated goods. No live data and no register results — pair it with screen_trademark, which checks the actual federal register. Use this to judge how protectable a name is; use screen_trademark to judge whether it conflicts. 5. compare_marks Compare two specific names side-by-side. Read-only, deterministic — the same two names always give the same scores. Returns JSON with visual similarity, Jaro-Winkler, phonetic (Soundex) similarity, an overall confusion score (0-1), and a risk level. Use to compare two names you already have in mind; use screen_trademark to discover conflicts for a name across the whole register (it also weighs classes and live/dead status, which this does not). Does not assess meaning, commercial impression, or class relatedness. 6. check_domains Check whether a brand name is free to register as a domain. Read-only. Returns JSON with one result per TLD (registered / available / unknown) — all TLDs are checked in parallel. Uses RDAP (the registry's own data, free, no key): 404 = not registered; 'unknown' = the TLD has no RDAP service. Covers .com/.io/.ai/.co/.app/.dev/.net/.org by default, or a custom TLD list. A free domain does NOT mean the trademark is clear, and a taken domain does not block the trademark — domains and trademarks are separate rights, so use screen_trademark for the trademark check. 7. check_global_marks Check a brand name against EU + UK trademark registers via TMview (EUIPO-operated, offices EM + GB). Read-only. Returns JSON with the EU/UK hits scored the same way as screen_trademark, plus the classes used. Use AFTER screen_trademark when you also sell in the EU/UK; the US screen is unaffected if TMview is down. BEST-EFFORT: TMview has no published API and resets connections from plain HTTP clients — when it will not answer, this returns { checked: false, reason } with a manual link instead of failing. A clear EU/UK result is a signal, not clearance. 8. request_watch_code Send a 6-digit verification code to an email address, for watch access. This sends an email (the only side effect) but creates nothing. Call it BEFORE list_watches, unwatch_mark, or attaching an email to a watch with watch_mark. The code expires in 10 minutes (5 tries); verifying it returns a 60-minute session token you can reuse for the other watch tools. A code is sent even if the email has no watches, so the response never reveals whether an address has watches. 9. watch_mark Start watching a mark for NEW confusingly similar filings. This CREATES a watch (a side effect — it stores the watch and sends a confirmation email with the stop link). Runs a baseline screen first — everything already on the register is marked seen, so you are only alerted on filings that appear AFTER the watch starts. Returns JSON with the watch id, its classes/threshold/schedule, and the baseline hits (for context). Check for new filings with check_watches, or let the scheduled checker run (daily by default, or weekly / every N days if you set a schedule). An email is required — it is the watch's owner, and the digest goes there (needs RESEND_API_KEY on the server; without it the watch still works and records hits, and alerts start once email is switched on). The email must be verified first — call request_watch_code, then pass the email and code (or the session token); without verification the watch is refused, so nobody can attach someone else's inbox. SCREEN ONLY — not clearance, not legal advice. 10. list_watches List the watches you ALREADY have — a read-only view, it does NOT check for new filings. Returns JSON with each watch's mark, classes, threshold, schedule, created/last-checked dates, total alerts so far, and the most recent new hits. Use this to see what you are watching; use check_watches to actually run a check for new filings right now. Private to one email — pass the email and the 6-digit code from request_watch_code, or a session token from a previous verification. No email addresses are ever returned. 11. unwatch_mark Stop watching a mark. This DELETES the watch (a side effect — it is removed and will no longer be checked). Returns JSON { removed, ok: true }. If the watch has an email, you must prove you own it — pass the email and the 6-digit code from request_watch_code, or a session token. A watch with no email needs no verification. 12. check_watches Run a check for NEW filings RIGHT NOW (on all your watches, or one by id) — this actually queries the register, unlike list_watches which only shows what you have. Returns JSON with only the filings that appeared since the watch started / last check, scored by risk. Use this when you want fresh results immediately; the scheduled checker also runs daily at 09:00 on each watch's own cadence (daily by default). SCREEN ONLY — not clearance, not legal advice.
Turn an English food description into an EFSA FoodEx2 code.
API discovery and x402 paid execution via MCP. Search by natural-language, call with USDC payment on Arbitrum, Base, BNB, Solana, SEI
Research briefs and source-linked literature comparisons via remote MCP. OAuth sign-in; research task execution uses RigorMed credits.
Ask Verse anything with sources, plus code review, translation and more paid per call over x402.
Search open model file records, inspect recorded SHA-256 hashes and license labels, and check estimated memory fit. Public reads need no account. Connect over Streamable HTTP. Public board and request tools require user consent. A matching hash checks bytes; fit and license labels do not establish successful execution or permission for every use. Hosted MCP: https://huggingbay.xyz/api/mcp Install: npx -y hugging-bay-mcp@0.1.13 Docs: https://huggingbay.xyz/docs Repository: https://github.com/barneywohl/hugging-bay
SEO site audit MCP: up to 5 supplied URLs for on-page issues, plus Lighthouse page-speed scores. On-page and technical SEO checks for up to 5 pages (status code, on-page score, title, meta description, H1, canonical, word count, links, load time and every failed check), plus Lighthouse scores and Core Web Vitals for a page. Use before publishing or after a migration to check up to 5 supplied URLs per audit, or inspect a page's speed. This is a focused SEO Data subset, not an automatic whole-site crawler. Distinguish Lighthouse lab checks from field measurements. Billing: paid data calls use API credits; get_api_credit_balance is free. The focused connections and SEO Data use the same balance and prices. Example prompts: - Audit the owned page I provide for title, headings and canonical issues after I approve the API-credit spend. - Within my approved API-credit budget, compare failed technical checks for up to five supplied pages. - After confirming the API-credit cost, report Lighthouse scores and available Core Web Vitals for my page, distinguishing lab checks from field data. Docs: https://docs.crakseo.com/mcp-servers/site-audit
# **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.
Find an HS code, HTS code or customs code, and read the customs duty or import tax.
Search and read the Pāli Canon: Pāli root texts with Russian and English translations.
Remote MCP server for Claude Code that finds Italian SMEs that may need the software you have already built, using public data, cited sources and three separate indices (opportunity, fit, evidence confidence). Outreach drafts respect Italian direct-marketing rules.
Search the official docs of Claude Code, Cursor, OpenAI Codex and MCP, refreshed daily.
SEO autopilot for a website: Site Health report and fix plan, Google Search Console data, keyword clusters, articles and draft scoring for Claude Code, Cursor and other AI agents.
Find your next B2B customers. Know why they fit. Describe the companies you want to reach. Leadbase researches matching businesses and relevant decision-makers, then saves the results with sources in an editable sheet. Start with 200 free credits in a new workspace and test your own target market. Qualify companies by the criteria that matter to your offer: services, region and publicly evidenced business signals. Research DACH SMEs and German craft businesses alongside other target markets. Turn existing accounts into a more useful prospect list. Enrich selected rows or entire columns, research relevant professional contacts and check available contact details. Review the evidence behind returned information before choosing your next step. Keep control of the result. Follow progress, edit your sheet, filter the list and export the data. Continue the same research instead of rebuilding the list each time. Use Leadbase with ChatGPT, Claude, Claude Code, Codex, Cursor and other compatible MCP clients. Connect your workspace and ask for a small list in your own target market. Research uses workspace credits.
Search EU public tenders from TED and national portals by CPV code, country, buyer or value.
Read reusable technical experience from other AI agents. Search a real problem with search_memories, then inspect_memory for provenance, evidence, reported outcomes and limitations. Seven anonymous read-only tools also support public agent discovery and Trust Passport inspection/verification. No account or credentials; no publishing, feedback or Candy actions on this endpoint. Operational telemetry may be recorded, but /mcp/chatgpt does not store search query text. Confidence and cryptographic integrity are not proof of truth, safety or independent validation. Writing requires the separate Remnant Agent OAuth connection at https://remnant.dedale-bi.com/mcp/agent-connect. Documentation: https://remnant.dedale-bi.com/connect. Apache-2.0 integration code and examples: https://github.com/Dedale-Project/remnant-connect. The hosted service, backend and knowledge are governed separately.
Search and read Linkbreakers docs, pricing and QR code templates. Read-only, no auth.
AI visibility for your brand: which buyer questions name you in ChatGPT, Perplexity, Claude and Google AI Overviews, which competitors AI recommends instead, which sources it cites, and what to fix first. OAuth sign-in with email and a one-time code.
Prop Firm Discount MCP provides structured data for current prop trading firm discounts, coupon codes, deals, promotions and events. Use it to find, search, compare, and verify active prop firm offers and discount codes.
Web scraping for agents. Point it at a URL and it returns the page as clean markdown, JavaScript-rendered pages included. Point it at a site and it maps the URLs or crawls the section you need in the background, a few pages at a time so results fit in the conversation. Search the web and read full pages, extract fields with a JSON schema you define (validated, never invented), read a store's catalogue or a blog's posts from the platform's own feed, and check whether a page has changed. Failed requests cost nothing. The free plan includes 1,500 credits a month.
Find what slows your website down. Run a free check in Claude Code, Cursor or ChatGPT. No account needed to try it. Save your result with a free Nimo account, then check again after your fixes. No card needed. Learn more: https://heynimo.com/for/coding-assistants
Find real discounts, promo codes and online deals with DiscountHub MCP.
Free AIOS discovery, preflight and bounded G05 authoritative-guidance execution for agents.
AI-powered eSIM recommendation agent for travelers. Provides real-time coverage checks, package search by country, and pricing across 190+ destinations via structured tool calls. Tools available: - list_countries - full list of supported destinations - check_coverage - network operators by country code - search_packages - filter eSIM plans by country - get_package_details - pricing and data specs - create_checkout - generate payment link for purchase No auth required for search tools. Ideal
Universal pay-per-call tool API for AI agents. Web search, price feeds, hive memory, LLM routing, code sandbox. Free tier (10 calls/day, no signup). x402 payments on Base + Solana.
Extension and app analytics across Chrome, Edge, Firefox, Google Play, and the Apple App Store. Search and compare extensions and apps; inspect trends, rankings, reviews, and version history; and search supported extension source code. Connect via Streamable HTTP with OAuth. API keys are also supported. Data availability and limits depend on the platform and plan. Documentation: https://chrome-stats.com/docs/mcp Privacy policy: https://chrome-stats.com/privacy Support: support@chrome-stats.com
Built for companies. Ready for AI agents. PaperOffice is the headless DMS your agent can actually operate: one MCP endpoint to search, read, upload, extract and sign business documents — no UI, no glue code. What the tools do: full-text and semantic search across workspaces · read existing OCR text without a new job · three-step upload with presigned URLs · AI-OCR (text, line boxes, tables) · structured extraction for invoices and 60+ document types (IDP) · PDF generation from Markdown/HTML · e
Search and read guides on Claude Code, Codex and Cursor, in English and Polish.
Search, read and cite technical books whose code examples run on each edition's pinned versions.
Tennessee Code Annotated (T.C.A.) — Tennessee state statutes by citation and by topic. Fleet #2885.
