Skip to main content
Glama
741,972 tools. Updated 2026-11-04 11:36

"A server for finding the latest documentation and best practices for a specific technology" matching MCP tools:

  • Search Bryntum product documentation for technical information. Use this to find API references, configuration options, examples, and best practices for Bryntum products like Scheduler, Scheduler Pro, Gantt, Calendar, Grid, and TaskBoard. Pass the library version you are using (usually found in package.json); use 'latest' if unknown.
    ConnectorNo auth
  • Finds a store by name and returns its current cashback rates from every cashback portal that lists it — online and in-store, percentage or fixed amount, with 'up to' flags — so the user can compare every portal and see the best. This is the preferred first call for any cashback question that names a store: 'best cashback for Walmart', 'highest Nike cashback', 'cashback at Expedia', 'Walmart cashback today', 'compare Walmart cashback portals', 'Best Buy in-store cashback', 'Dell cashback in Germany'. No prior lookup is needed — do not call get_stores_by_name, get_stores_by_country or get_countries first. Returns every matching store (best match first, one entry per country), each with its 'cashback_rates'; an empty list means no match — retry with a shorter name or without country_code. Use get_cashback_rates_by_store_id only when a store_id is already known, get_gift_cards_by_store_name for gift card discounts, and get_best_deals_by_brand when the user asks where to buy a brand's products rather than about a specific store. Rates reflect GotCashback's current data, refreshed several times a day. Present every returned portal's rate to the user (a table with a link column, not only the best one) and always show each rate's 'url' as a clickable link — cashback is only credited when the user clicks through it.
    ConnectorNo auth
  • Should I bet this? One-call verdict for a specific bet. Returns the no-vig fair price for the exact bet, the best available price and which book has it, how the user's price (if given) grades as EV, a line-shopping nudge, and a plain-English call: BET / LEAN / FAIR / PASS (or NO_DATA). Use this when a user asks whether a specific bet is worth making, or whether they're getting a good number, instead of stitching /ev + /consensus + /best-line yourself. The best-price / shop recommendation is scoped to books the user can bet at (default US, so a US bettor is never told to use a euro book). Set it once with parlayapi_set_bettable_books and it is remembered per key, or pass region / books here per call. Args: sport: sport_key, e.g. "baseball_mlb". side: the team you'd bet (h2h / spreads), or "over" / "under" (totals / props). market: h2h | spreads | totals | a player-prop key (player_hits, player_points, ...). home, away: the two teams, to identify the game. Or pass `team` with one name. team: one team name to find the game (alternative to home + away). player: player name (required for player-prop markets). line: the number for spreads, totals, or props. book: the book you'd bet at (grades that book's current price). price: the price you're offered (American like -110, or decimal like 1.91). Overrides `book`, use it to grade a specific number in hand. region: where you can bet: us (default) | eu | uk | au | ca. books: exact CSV of books you can bet at (overrides region; use for state-level geo-blocks, e.g. "draftkings,fanduel,novig"). bankroll: the user's bankroll; when the bet is +EV, returns a suggested Kelly stake amount ("bet it, ~$X"). kelly: Kelly fraction (default 0.5 = half-Kelly, the bankroll-safe standard). The response also carries an `edge_alert` when a book shows a price far better than the market (a possible soft error worth grabbing, or a stale line to verify) that the normal best-price guard would otherwise hide.
    ConnectorNo auth
  • Finds a store by name and returns its current cashback rates from every cashback portal that lists it — online and in-store, percentage or fixed amount, with 'up to' flags — so the user can compare every portal and see the best. This is the preferred first call for any cashback question that names a store: 'best cashback for Walmart', 'highest Nike cashback', 'cashback at Expedia', 'Walmart cashback today', 'compare Walmart cashback portals', 'Best Buy in-store cashback', 'Dell cashback in Germany'. No prior lookup is needed — do not call get_stores_by_name, get_stores_by_country or get_countries first. Returns every matching store (best match first, one entry per country), each with its 'cashback_rates'; an empty list means no match — retry with a shorter name or without country_code. Use get_cashback_rates_by_store_id only when a store_id is already known, get_gift_cards_by_store_name for gift card discounts, and get_best_deals_by_brand when the user asks where to buy a brand's products rather than about a specific store. Rates reflect GotCashback's current data, refreshed several times a day. Present every returned portal's rate to the user (a table with a link column, not only the best one) and always show each rate's 'url' as a clickable link — cashback is only credited when the user clicks through it.
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.
    1
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.
    18
    616 npm
    1
    MIT

Matching MCP Connectors

  • Returns the plain-language meaning and step-by-step fix for one Malinois finding. Use it while helping the user fix an issue reported by scan_app, or when they ask what a finding means. Pass the rule_id exactly as scan_app returned it. Read-only, no network, instant.
    ConnectorNo auth
  • Validate HTTP security headers you provide (JSON): CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Permissions-Policy, Referrer-Policy against best practices. Use to test header config before deployment or validate non-public servers; use scan_headers to fetch live. Free: 30/hr, Pro: 500/hr. By default header values are truncated to 500 chars; pass include='full' for the full raw value. Returns {total, by_severity, findings}. No external requests.
    ConnectorNo auth
  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
    ConnectorNo auth
  • Full-text search across all SEC EDGAR filings since 2001 for a keyword or phrase. Wraps EDGAR's own full-text search index, so it covers every filer and form type, not just a single company. Useful for finding who is disclosing a particular risk, technology, litigation, or event across the entire market. When to use: cross-company research ("who is disclosing AI-related risk factors"), finding filings that mention a specific term, litigation or regulatory tracking. When NOT to use: you already know the company (use edgar_filings_feed, which is company-scoped and cheaper), or you need results from before 2001 (EDGAR full-text search does not cover that far back). Args: - query (string, required): search text. Wrap an exact phrase in double quotes, e.g. "\"material weakness\"". - forms (string[], optional): restrict to form types, e.g. ["10-K"]. - dateFrom (string, optional): ISO start date (YYYY-MM-DD). - dateTo (string, optional): ISO end date (YYYY-MM-DD). - limit (integer, optional, default 10): maximum hits to return (1-50). Returns structuredContent: { "query": "material weakness", "totalMatches": 10000, "totalIsApproximate": true, "count": 2, "hits": [ { "id": "0001193125-26-123456:doc.htm", "entity": "Example Corp.", "form": "10-K", "filedAt": "2026-03-01", "cik": "0000320193" } ], "source": "https://www.sec.gov/edgar" } "totalMatches" is a lower bound and "totalIsApproximate" is true once EDGAR's own count exceeds its display cap (10,000) — narrow with forms/dateFrom/dateTo for a precise count.
    ConnectorNo auth
  • List the repository's generated documentation as a browsable table of contents - every doc page, not a query-filtered subset. Read-only; no side effects. Returns Markdown grouped by section, each entry with its title, slug, repository path, and source paths, plus the total count and a pagination cursor so you can tell whether more pages remain (no silent truncation). Use this to see what docs already exist before adding one (so you don't duplicate) or to find the slug to pass to propose_doc_update; when you are hunting for a specific topic, search_docs is more direct.
    ConnectorNo auth
  • List the repository's generated documentation as a browsable table of contents - every doc page, not a query-filtered subset. Read-only; no side effects. Returns Markdown grouped by section, each entry with its title, slug, repository path, and source paths, plus the total count and a pagination cursor so you can tell whether more pages remain (no silent truncation). Use this to see what docs already exist before adding one (so you don't duplicate) or to find the slug to pass to propose_doc_update; when you are hunting for a specific topic, search_docs is more direct.
    ConnectorNo auth
  • Finds where to buy products from a shopping category with the most savings: returns the matching categories and, for each, the stores in it ranked by best current cashback rate, then best gift card discount. Use it when the user names a type of product or a category rather than a store or brand — 'where can I buy dog food with the biggest discount?', 'best cashback for electronics', 'travel booking sites with cashback'. For a specific retailer use get_cashback_rates_by_store_name; for a product brand use get_best_deals_by_brand. Returns up to 5 matching categories, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).
    ConnectorNo auth
  • Finds where to buy products from a shopping category with the most savings: returns the matching categories and, for each, the stores in it ranked by best current cashback rate, then best gift card discount. Use it when the user names a type of product or a category rather than a store or brand — 'where can I buy dog food with the biggest discount?', 'best cashback for electronics', 'travel booking sites with cashback'. For a specific retailer use get_cashback_rates_by_store_name; for a product brand use get_best_deals_by_brand. Returns up to 5 matching categories, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).
    ConnectorNo auth
  • Return the holdings this user has already registered in FinBridge with import_portfolio — listed stocks plus cash, crypto, ETF and physical assets — valued at the latest prices, with return and asset allocation. A user who has registered nothing gets an empty list. Not this tool for: analysing or valuing a company (get_valuation), prices (get_stock_prices), or finding companies (search_dart_company / search_edgar_company). It reads only what this user stored, so it knows nothing about a company they do not hold. Crypto and ETFs use live ccxt quotes, stocks the latest close in the database, cash and physical assets the registered amount. allocation is aggregated per currency; combined converts everything to KRW using an ECB-derived USD/KRW rate.
    ConnectorAPI key
  • Start here before reading, writing or changing a pricing equation. Returns the TypeScript contract the equation runs against (specification, revision, requisition, customer, workflow, done(), variable(), round, useDimension, createBands; for scope ORDER: parts, subtotal, customer, addLineItem), narrowed to the given scope + ownerId: its technology, material names and material variable names, lead-time names, and which modules the manufacturer has. Explains the loop: save(entity=typescriptEquation) to validate and store a draft, generateQuote(equationId) to test it, then — only on the manufacturer's explicit request — publishEquation to make it live. Pass includeSource=true to also get the live equation's source, or equationId=<id> to get the source of one specific equation (a draft, for example) with its live/not-live state.
    ConnectorAPI key
  • Use this when the user asks which companies use a particular technology (for example Intercom, Zendesk, HubSpot, Shopify, Stripe), or which technologies are most used. With a slug: companies detected using that technology, 20 per page. company_count is every company detected using it; listed_count is how many the list can page through, so stop at page ceil(listed_count / 20). Without a slug: the technology index, most-used first, with company counts (default 100, up to 1,000). Slugs are lower-case with hyphens, e.g. intercom, hubspot, google-analytics, shopify. Works without an API key; no contact reveals.
    ConnectorOAuth
  • Start here before reading, writing or changing a pricing equation. Returns the TypeScript contract the equation runs against (specification, revision, requisition, customer, workflow, done(), variable(), round, useDimension, createBands; for scope ORDER: parts, subtotal, customer, addLineItem), narrowed to the given scope + ownerId: its technology, material names and material variable names, lead-time names, and which modules the manufacturer has. Explains the loop: save(entity=typescriptEquation) to validate and store a draft, generateQuote(equationId) to test it, then — only on the manufacturer's explicit request — publishEquation to make it live. Pass includeSource=true to also get the live equation's source, or equationId=<id> to get the source of one specific equation (a draft, for example) with its live/not-live state.
    ConnectorAPI key
  • Validate JSON-LD structured data against Schema.org rules and AI-citation best practices. Accepts either a URL (fetched) or a raw JSON string (parsed directly). Read-only when given `url` (one HTTP GET). Zero network when given `schema_json`. No writes. Deterministic, rule-based; no LLM. Validates required/recommended properties, @context correctness, sameAs links, and AI-search-friendly patterns. When to use: focused JSON-LD audits, or to validate a schema block you're about to ship. For a full page audit that includes schema + everything else, use `audit_page` instead. Either `url` or `schema_json` must be provided (not both). If both are provided, `schema_json` wins and no fetch happens.
    ConnectorNo auth
  • Keyword search over the list of places to submit a startup. A place's exact name or website ("Indie Hackers", "indiehackers.com") puts it first. Asking for free ("free", "no cost", "$0") leaves out places that are paid only. Product words ("web app", "SaaS", "AI tool", "mobile app") keep only places that take that kind of product. Kind-of-place words ("launch site", "directory", "community") put places of that kind first. Other words match names, websites, regions, and the list's notes. For example "free launch sites for a web app", "AI tool directories", or "Australia". Returns up to 20 places, best match first, each with id, title, url (its row on submitmystartup.com, for citing), and a one-line summary. A query with no specific words returns the best free places. Use fetch with an id for the full record, and find_directories to shortlist by a founder's product and limits.
    ConnectorNo auth
  • Use this when the user asks which of a creator's, competitor's or their own posts performed best or beat the account's normal, or what works for an account before writing. Scores the latest 20, 30, 50 or 100 posts against that account's own median and says by how much each beat it. About 3-4 credits for 30 posts on Instagram or TikTok, none on YouTube, more on Facebook. Longer runs return a `job_id` for xcut_get_job. Do not use for a full metrics table (use xcut_profile_analytics) or for a topic across many accounts (use xcut_search_viral).
    ConnectorNo auth