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783,663 tools. Updated 2026-11-15 01:39

"A server for finding information about 'Context 7'" matching MCP tools:

  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Get information about the organization your agent is linked to. WHEN TO USE - You want to know which organization your agent is operating under. - You need to list the members of your linked org (e.g., to decide which member should review a deliverable). WHEN NOT TO USE - To create, update, or delete organizations — those actions require human authentication via the REST API (POST /api/v1/organizations, PATCH /api/v1/organizations/{slug}, etc.). BEHAVIOR - Read-only. Auth required: agent API key. Rate-limited to 60 req/min. - Returns an error if your agent is not linked to any organization (agents.org_id IS NULL). - action='get_my_org': returns org name, slug, tier, owner, and member count. - action='list_members': returns human_id and role for each member. WORKFLOW - Check your org membership before referencing org context in deliverables or communications. - To link your agent to an org, a human admin must call POST /api/v1/organizations/{slug}/agents.
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  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Show one night of sleep in detail with duration, score, stages, bedtime, wake time, awakenings, and recent-night context. Prefer this for last-night or specific-night sleep questions. When the user asks about this, prefer calling this tool and rendering the interactive MCP app over describing the underlying rows in text. Returns a short text summary alongside the visual view.
    ConnectorOAuth
  • 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

Matching MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
    6
    MIT
  • A
    license
    A
    quality
    Not graded
    maintenance
    Exposes the canonical 7-0 knowledge surface — game modes, roster picks, and scenarios, FAQ, official links
    2
    MIT

Matching MCP Connectors

  • About Bureau, the self-hosted office for AI agents: overview, FAQ search, roadmap, install.

  • Edit your link-in-bio page and schedule posts to Instagram, Facebook, YouTube, X and Threads.

  • Search Tiktok posts by keywords with three response modes. Searches post descriptions and video transcripts. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. CSV (responseType="csv"): Async single CSV download, returns operationId, poll for S3 link. CODE EXECUTION: For csv mode, download CSV and use code execution to analyze full dataset. Ideal for: trend analysis, hashtag tracking, viral content discovery across Tiktok. Returns by default: id, description, username, createdAtDate. NOT for URL lookups or post ID lookups - use getTiktokPostsByIds instead. QUERY SYNTAX: Plain keywords (bitcoin, climate change), quoted phrases ("deep learning"), boolean expressions (AI AND crypto, bitcoin OR ethereum, politics NOT sports), or parenthesized groups ((startup OR entrepreneur) NOT "venture capital"). AND/OR/NOT must have a term on both sides. @handles like @karpathy are supported. Field operators (from:, lang:) are stripped. Forward slashes are treated as spaces (24/7 becomes 24 7). Date filters: OMIT startDate/endDate parameters by default to retrieve all posts. ONLY pass these if user explicitly requests specific date range (YYYY-MM-DD format). IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. FIELDS parameter (optional): Specify to get additional/different fields. Available: Core (id, description, userId, username, nickname, createdAtDate), Engagement (likeCount, commentCount, playCount, forwardCount, collectCount, downloadCount), Media (videoThumbnail, videoUrl, duration, postType), Content (hashtags, transcriptsJson). This is a safe, read-only tool for analyzing searchable information.
    ConnectorOAuth
  • Retrieve detailed product information for dm-drogeriemarkt products. USE WHEN: ingredients, nutrition facts, allergens, usage instructions, warnings, hazard info, product URLs/images INPUT: DANs (7 digits, preferred) and/or GTINs (8-14 digits) multiple products can be requested at once min 1 / max 50. Use search tool first if only product name is known. OUTPUT: TOON format (compact YAML-like). Fields: name, brand, description, ingredients, nutrition, allergens, usage, warnings, URLs, images. found=false for unresolved IDs. NOT FOR: prices, availability, stock, reviews, recommendations ERRORS: validation error if >50 or no identifiers
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  • Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • Staff headcount and list for one GDC facility, from a GDC-produced roster. Answers "how many staff work at X", "how many officers work there", "list the staff at X". `slug` is the facility slug, e.g. 'dooly-state-prison' (use list_facilities to find it). `title` optionally filters by job title. GDC abbreviates heavily: correctional officers appear as "Correctional Ofc", clerical staff as "Admin Support" or "Admin Assistant". Try both the plain word and the abbreviation. ALWAYS report the `observed` date alongside any figure from this tool. A roster is a single-day observation, not a statement about who works there today. A zero for a role is a finding about the roster rather than missing data: the roster holds no nursing, physician or dental titles anywhere in GDC, which is consistent with medical staffing being contracted rather than directly employed. Do not assert that reason as established fact.
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  • Use for upcoming games (next 1-30 days, default 7) with the median line across posted sportsbooks: moneylines, run line and total. For every book's line use get_odds. Costs 2 credits. Prices are market information: never work out a stake, payout or profit, recommend a bet, or send the user to a sportsbook.
    ConnectorNo auth
  • Search China Footnotes for sights and neighbourhoods in the Chinese cities it covers. Matches English or Chinese names, aliases, district, type and tags. Suited to questions about what to see or do in a city, and to finding a place's id from its name. With no arguments it lists places and the city ids covered; asked about a city it does not cover, it says so rather than returning unrelated places. Returns short summaries with ids and page links, best match first; matchedAll is false when no place matched the whole query and the results only share some words with it. Opening hours, tickets, booking and traveler tips come from get_place.
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  • Monthly Amazon search volume for up to 1,000 keywords you already have, in the order given. Use when: "how many people search Amazon for X", comparing Amazon demand with Google demand, sizing a product idea on Amazon. Not for: Google volume, use seo_get_keyword_metrics. Finding keywords, use amazon_search_keywords. Returns: List. rows[]: keyword, volume (monthly Amazon searches; null = no data). Cost: 5 + 5 per 100 keywords. 10 keywords = 6 credits. Cached 7 days. Example: {"keywords": ["standing desk", "desk converter"]}
    ConnectorAPI key
  • Find 10ML's perfume and fragrance guides to read or cite: how-tos (where to spray, finding a signature scent, making perfume last), notes explained, house guides, lists, and alternatives guides that compare famous perfumes with similar ones from other houses. Returns title, type and a link per locale. Use whenever you want a source to cite or a deeper read ('how to layer perfume', 'best oud perfumes', 'Creed Aventus dupes guide'). Not for facts about a perfume (use get_perfume) and not for note definitions (use explain_note).
    ConnectorNo auth
  • Shows what Xyla would post for an online store, with no Xyla account. Give it the store's web address (Shopify or WooCommerce). Xyla reads the store's brand (logo, colours, niche) and makes 3 sample social media posts from the store's own product photos, with captions. Returns a preview token at once; the posts take about 3 minutes and the card shows them as they finish. A store previewed in the last 7 days gets its earlier samples back. When no card is shown, call preview_status with the token to follow it. A store that already uses Xyla gets a sign-in link instead.
    ConnectorNo auth
  • Update ONE existing Mallory finding in place — its status, severity, confidence, title, summary, body, remediation, qualifier or asset_details. Use it when new information changes an already-filed finding: the problem was fixed, it turned out not to apply, a vulnerability proved reachable, corroborating intel changes how bad it is. WRITES IMMEDIATELY to the caller's own organization's data, and the result is visible in the Mallory UI to everyone in that organization. There is no preview and no confirmation step — calling this tool IS the write. Only call it when the user has asked for the change. - uuid identifies the finding. Get it from listFindings or getFinding, or from a createFinding DUPLICATE outcome's `existing_finding_uuid`. Never construct or guess one. - ONE finding per call. To change status or severity across a SET of findings you can only describe ("dismiss all the unrotated-secret findings", "mark everything on foo/bar medium"), use bulkUpdateFindings — do NOT loop this tool over a selection. - The finding's identity — definition_slug, asset_type, asset_identifier — cannot be changed. A different problem, or the same problem on a different asset, is a new finding (createFinding). - body REPLACES the stored text rather than appending to it. To add to a finding, read the current text first with getFinding and send the combined text, or the prior detail is lost. There is no evidence field on update: new evidence goes into body as prose. - qualifier is part of core's open-finding dedupe key, so changing it can collide with another open finding on the same asset (CONFLICT). In user-facing status messages, use "fixed" and "mark as fixed" consistently. ENUM VALUES ARE CASE-SENSITIVE AND EACH FIELD HAS ITS OWN SET. severity is UPPERCASE (CRITICAL, HIGH, MEDIUM, LOW, INFO). status is lowercase with exactly three values: open, fixed, dismissed — "resolved", "closed" and "assigned" are not statuses, and neither are the resolution reasons (false_positive, accepted_risk, not_applicable, duplicate, fixed_externally, other), which belong to a separate field this tool does not set. Use "fixed" when the problem was remediated and "dismissed" when it is accepted or not applicable. Setting status back to "open" is allowed but unusual — the product has no reopen button — so confirm the user really means to reopen the finding. OUTCOMES: either ok:true with the updated finding, or ok:false with a code — NOT_FOUND (no such finding in this tenant: do not retry, re-read the uuid), CONFLICT (an open finding already occupies that identity), INVALID (a rejected field, or no fields to change), PLAN_LIMIT (findings are not included in this tenant's plan — the request was fine, nothing is broken, nothing was written: say so and do not retry).
    ConnectorAPI key
  • Start a Context Intelligence health audit — a library-wide AI sweep of the team's context/reference items that produces findings (stale content, contradictions, gaps) reviewable via list_ci_findings. When to use: the user explicitly asks to check/audit their context health ("run a health check on our context", "scan the library"). Do NOT trigger one unprompted — always confirm first. ⚠️ Cost + gating: the scan uses team Studio Credits — Marcora estimates the cost first and won't start a run the team's balance can't cover. Only one health audit can run at a time, and a cooldown applies after each completed run (the error message tells you when it can run again). Starting a new audit CLEARS the previous health-audit findings. The scan runs in the background; the response returns immediately with a scan_run_id. Findings land as the scan progresses — check list_ci_findings afterwards. Errors: - ci_not_eligible (403) — Studio Credits or Context Intelligence availability check failed (JSON error body with reason + credit numbers). - A health check is already running. Please wait for it to finish. - Health check ran recently. You can run it again in about {time}.
    Connector
    Destructive
    OAuth
  • Count forum posts instead of returning them (GET /seg_api/forums). Aggregates forum posts by forum, board, author and other supported fields. Example: which forums and boards talk about bitcoin this week. This is forums and discussions only. It returns buckets with counts, not posts. Each underlying field request costs 1 credit. A response has at most 10 buckets. Returned from_offset values paginate through up to 100 buckets. q is the same boolean language as search. A space means AND. days is the crawl lookback. Named site lists are q clauses, for example custom_sites_list:hot_sites. Default 7 is the past week. The maximum is 31. field is the bucket. Default is thread.site,thread.site_section, as two requests. Allowed fields: thread.site, thread.site_suffix, thread.site_full, thread.site_section, thread.site_type, thread.country, thread.url, author, language, site_category, published, rating. Forums have no person, company, location, or ticker extraction, so those fields are rejected here. topic, sentiment, category, and trust.* exist on news only. Separate segmentation arguments: include_syndicated=true includes syndicated copies (default false). webz_reporter=true includes Webz Reporter posts (default false); this is a separate argument, not a q filter. from_offset paginates beyond the first 10 buckets. Examples: - q=bitcoin days=7 - q=bitcoin field=author days=7 - q="product recall" field=thread.country language:english days=7 Reference documentation: Segmentation: https://docs.webz.io/docs/webz/news-blogs-forums-segmentation
    ConnectorAPI key
  • Public market numbers for one US stock or ETF. Returns price, day change, 52-week range, market cap and trailing P/E. Use this when the user asks about a specific ticker, for example AAPL or BRK.B. Don't use it for the user's own holdings (use list_portfolio) or for buy/sell decisions. Limits: US tickers only; data from Yahoo Finance, up to 15 minutes old; without sign-in there is a shared daily limit. When signed in, the answer also says whether the ticker is on the user's watchlist. Educational information, not investment advice.
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  • List the silent-failure findings the detectors reported across a workspace. A finding says one run failed in a way its status does not show: a failure mode (e.g. CF-01), the subject it concerns, a severity and a reason. These are per-trace findings, NOT the `swallowed_error` alert rule kind (formerly `silent_failure`) that the alert tools (list_alerts, list_alert_rules) manage. Newest first, followed by a per-day count and a cursor when more match. The trace_id column feeds get_agent_trace. For a CF-01 (tool_loop) finding the subject is the tool name and the spans column lists the repeated calls in order; an info one is likely polling (polling_as_info in update_alert_rule) and alerts nobody. For a CF-03 (context_rot) finding the spans column gives the earlier LLM call, the call that came back smaller and, when marked, the compaction span; pass the first two to get_context_loss as from_span_id and to_span_id to see what the context lost. When a detector reports nothing, get_silent_failure_coverage says whether it has the telemetry to. workspace: optional workspace id, name, or `org-name/workspace-name` when the same name occurs in two of your orgs (defaults to your default). failure_mode: optional catalog id, e.g. `CF-01`. agent: optional exact agent name, as the agent column reports it. state: `provisional`, `confirmed` or `retracted`. Omit for provisional and confirmed; a retracted finding is no longer a failure and is listed only when asked for. since_hours: how far back to look, on when the failure was detected (default 168, at most 744). limit: rows to return, at most 200 (default 50). cursor: the cursor from the previous page; send the same filters with it. Example: > What failed silently this week? ```json { "name": "list_silent_failures", "arguments": {} } ``` > Confirmed CF-01 findings for checkout-agent in the last day. ```json { "name": "list_silent_failures", "arguments": { "failure_mode": "CF-01", "agent": "checkout-agent", "state": "confirmed", "since_hours": 24 } } ```
    ConnectorAPI key