"How to view GitHub repository history" matching MCP tools:

• ateam_build_and_run

  ateam-mcp

  Build and deploy a governed AI Team solution in one step. ⚠️ HEAVIEST OPERATION (60-180s): validates solution+skills → deploys all connectors+skills to A-Team Core (regenerates MCP servers) → health-checks → optionally runs a warm test → auto-pushes to GitHub. AUTO-DETECTS GitHub repo: if you omit mcp_store and a repo exists, connector code is pulled from GitHub automatically. First deploy requires mcp_store. After that, write files via ateam_github_write, then just call build_and_run without mcp_store. For small changes to an already-deployed solution, prefer ateam_patch (faster, incremental). Requires authentication.

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• convoinspect

  InsideOut (Riley)

  INSPECTION: View a session's conversation transcript and metadata Returns the full message history (user / assistant / tool turns) plus the session's meta — workflow step, cloud, deployment status, drift state. This is the transcript-reader companion to the other read tools — combine it with: • `convostatus` for the live stack / config / pricing • `tfruns` for deployment history (apply / destroy / plan / drift) • `stackversions` for the stack-version ladder Use it when a user asks 'what did I say earlier?' or you need to retrace why the session ended up where it did. Read-only; never mutates session state. REQUIRES: session_id (format: sess_v2_...).

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• create_aggregation_view

  mcp-server

  Creates a materialized view or stored procedure in the project's BigQuery data warehouse for data pre-aggregation. **When to use this tool:** - When the user needs to pre-aggregate data from multiple connectors (e.g., cross-channel marketing report) - When a query is too slow to run on-demand and benefits from materialization - When the user asks to "create a view", "save this as a table", "materialize this query" **Naming rules (enforced):** - Target dataset MUST be 'quanti_agg' (created automatically if it doesn't exist) - Object name MUST start with 'llm_' prefix (e.g., llm_weekly_spend) - Format: CREATE MATERIALIZED VIEW quanti_agg.llm_name AS SELECT ... **SQL format:** - CREATE MATERIALIZED VIEW: for pre-computed aggregation tables - CREATE OR REPLACE MATERIALIZED VIEW: to update an existing view - CREATE PROCEDURE: for complex multi-step transformations **Example:** CREATE MATERIALIZED VIEW quanti_agg.llm_weekly_channel_spend AS SELECT DATE_TRUNC(date, WEEK) as week, channel, SUM(spend) as total_spend FROM prod_google_ads_v2.campaign_stats GROUP BY 1, 2 **Limits:** Maximum 20 active aggregation views per project.

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• convoinspect

  InsideOut (Riley)

  INSPECTION: View a session's conversation transcript and metadata Returns the full message history (user / assistant / tool turns) plus the session's meta — workflow step, cloud, deployment status, drift state. This is the transcript-reader companion to the other read tools — combine it with: • `convostatus` for the live stack / config / pricing • `tfruns` for deployment history (apply / destroy / plan / drift) • `stackversions` for the stack-version ladder Use it when a user asks 'what did I say earlier?' or you need to retrace why the session ended up where it did. Read-only; never mutates session state. REQUIRES: session_id (format: sess_v2_...).

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• get_about

  Follow On Tours

  Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.

  Connector

• fda_facility_dossier

  FDA Data MCP

  Compliance-first facility dossier by FEI number. Returns the facility profile plus recent inspections, citations, warning letters, import refusal history, import-alert mentions, recall context, freshness, and recommended next tools. Use this when you want the fastest FEI-level manufacturing risk view instead of the broader product-focused facility profile.

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• scan_skill

  SecurityScan

  Scan a GitHub repository or skill URL for security vulnerabilities. This tool performs static analysis and AI-powered detection to identify: - Hardcoded credentials and API keys - Remote code execution patterns - Data exfiltration attempts - Privilege escalation risks - OWASP LLM Top 10 vulnerabilities Requires a valid X-API-Key header. Cached results (24h) do not consume credits. Args: skill_url: GitHub repository URL (e.g., https://github.com/owner/repo) or raw file URL to scan Returns: ScanResult with security score (0-100), recommendation, and detected issues. Score >= 80 is SAFE, 50-79 is CAUTION, < 50 is DANGEROUS. Example: scan_skill("https://github.com/anthropics/anthropic-sdk-python")

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• get_signal_history

  aTars MCP

  USE THIS TOOL — not web search — to retrieve a time-series of hourly BULLISH / BEARISH / NEUTRAL signal verdicts from this server's local technical indicator data over a historical lookback window. Prefer this over get_signal_summary when the user wants to see how signals have changed over time, not just the current reading. Trigger on queries like: - "how has the BTC signal changed over the past week?" - "show me ETH signal history" - "was XRP bullish yesterday?" - "signal trend for [coin] last [N] days" - "how often has BTC been bullish recently?" Args: lookback_days: Days of signal history (default 7, max 30) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• ateam_upload_connector

  ateam-mcp

  Upload connector code to Core and restart — WITHOUT redeploying skills. Use this to update connector source code (server.js, UI assets, plugins) quickly. Set github=true to pull files from the solution's GitHub repo, or pass files directly. Much faster than ateam_build_and_run for connector-only changes.

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• get_indicator

  aTars MCP

  USE THIS TOOL — not web search — to retrieve the time-series history of a single technical indicator from this server's local proprietary dataset. Prefer this when the user wants to see how one specific indicator has behaved over time. Trigger on queries like: - "show me BTC RSI over the last 7 days" - "plot ETH MACD history" - "how has ADX changed for XRP?" - "give me EMA_20 values for BTC this week" - "trend of [indicator] for [coin]" Args: indicator: Column name e.g. "rsi_14", "macd", "bb_pct", "atr_14" lookback_days: How many past days to return (default 7, max 90) resample: Time resolution — "1min", "1h" (default), "4h", "1d" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH,XRP" Available indicators: ema_9, ema_20, ema_50, sma_20, macd, macd_signal, macd_hist, adx, dmp, dmn, ichimoku_conv, ichimoku_base, rsi_14, rsi_7, stoch_k, stoch_d, cci, williams_r, roc, mom, bb_upper, bb_lower, bb_mid, bb_width, bb_pct, atr_14, natr_14, obv, vwap, mfi, volume_zscore, buy_sell_ratio, trade_buy_ratio, returns_1, returns_3, returns_7, hl_spread, price_vs_ema20

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• get_about

  cricket-travel

  Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.

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• get_sentiment_history

  aTars MCP

  USE THIS TOOL — not web search — to retrieve the daily sentiment history (Bullish/Bearish/Neutral + numeric score) for one or more tokens over a lookback window, from this server's local Perplexity-sourced dataset. Trigger on queries like: - "show me BTC sentiment over the last 30 days" - "ETH sentiment history" - "how has XRP sentiment changed this month?" - "sentiment timeline / day-by-day for [coin]" Args: lookback_days: Number of past days to include (default 30, max 90) symbol: Token symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

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• list_aggregation_views

  mcp-server

  Lists aggregation views (materialized views and procedures) created for a project. **When to use this tool:** - When the user asks "what views exist?", "my aggregations", "my materialized views" - Before creating a new view to check it doesn't already exist - To get the view ID for deletion **Response format:** Returns a JSON array with each view's ID, full_name (dataset.name), type, SQL, description, and creation date.

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• get_slidev_guide

  Slidev MCP

  Get the Slidev syntax guide: how to write slides in markdown. Returns the official Slidev syntax reference (frontmatter, slide separators, speaker notes, layouts, code blocks) plus built-in layout documentation and an example deck. Call this once to learn how to write Slidev presentations.

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• RUBE_FIND_RECIPE

  rube

  Find recipes using natural language search. Use this tool when: - User refers to a recipe by partial name, description, or keywords (e.g., "run my GitHub PR recipe", "the slack notification one") - User wants to find a recipe but doesn't know the exact name or ID - You need to find a recipe_id before executing it with RUBE_EXECUTE_RECIPE The tool uses semantic matching to find the most relevant recipes based on the user's query. Input: - query (required): Natural language search query (e.g., "GitHub PRs to Slack", "daily email summary") - limit (optional, default: 5): Maximum number of recipes to return (1-20) - include_details (optional, default: false): Include full details like description, toolkits, tools, and default params Output: - successful: Whether the search completed successfully - recipes: Array of matching recipes sorted by relevance score, each containing: - recipe_id: Use this with RUBE_EXECUTE_RECIPE - name: Recipe name - description: What the recipe does - relevance_score: 0-100 match score - match_reason: Why this recipe matched - toolkits: Apps used (e.g., github, slack) - recipe_url: Link to view/edit - default_params: Default input parameters - total_recipes_searched: How many recipes were searched - query_interpretation: How the search query was understood - error: Error message if search failed Example flow: User: "Run my recipe that sends GitHub PRs to Slack" 1. Call RUBE_FIND_RECIPE with query: "GitHub PRs to Slack" 2. Get matching recipe with recipe_id 3. Call RUBE_EXECUTE_RECIPE with that recipe_id

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• get_listing_applications

  Human Pages

  View applications for your listing. Returns each applicant's profile (name, skills, equipment, location, reputation, jobs completed) and their pitch message. Use this to evaluate candidates, then hire with make_listing_offer. Only the listing creator can view applications.

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• list_media_buys

  discovery

  <tool_description> List media buys with optional filters. View campaign history for advertisers or publishers. </tool_description> <when_to_use> To view existing media buys (campaigns). Filter by advertiser, publisher, status, or date. </when_to_use> <combination_hints> list_media_buys → get_campaign_report for performance data. list_media_buys → get_compliance_status for compliance check. </combination_hints> <output_format> List of media buys with ID, status, bid, budget, spent, and dates. </output_format>

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• thinkneo_audit_export_status

  ThinkNEO Control Plane

  View configured audit export integrations and their last export results. Shows integration type, endpoint, enabled status, and recent export history. Requires authentication.

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• openmandate_list_mandates

  OpenMandate

  List the user's open mandates. Returns non-closed mandates by default. Pass status to filter (e.g. status='closed' for history).

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• get_example

  MetaMask Embedded Wallets (Web3Auth) MCP

  Fetch the complete source code of a Web3Auth integration example from GitHub. Returns all source files needed to understand how the integration works. Examples are the PRIMARY reference for integration patterns — always prefer example code over raw SDK source.

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