"Finding people on GitHub" matching MCP tools:

• automation_list

  Perspective AI

  Lists every automation configured on a perspective with its trigger, channel (sensitive details redacted), execution mode, enabled state, schedule description, and recent error/success metadata. Behavior: - Read-only. - Errors when the perspective is not found or you do not have access. - Sensitive parts of channel delivery (e.g., webhook auth headers, full URLs) are redacted before being returned. - has_error / last_error / last_error_at / failure_count appear only when there have been recent failures. When to use this tool: - Auditing what's wired up on a perspective before adding more automations. - Finding an automation_id to feed into automation_update, automation_delete, or automation_test. - Diagnosing a failing automation via last_error / failure_count. When NOT to use this tool: - Creating a new automation — use automation_create. - Toggling enabled or changing config — use automation_update. - Verifying delivery actually works — use automation_test.

  Connector

• 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.

  Connector

• group_discovery_scan

  DialogBrain

  Scan a group to evaluate its quality before joining. Fetches recent messages, analyzes activity, spam, and engagement, then returns a quality score and plain-English verdict. When to use: - After finding groups with group_discovery.search - Before deciding which groups to join Returns: overall_score (0-1), is_disqualified, disqualify_reasons, individual scores, and a verdict string.

  Connector

• search_officers

  openregistry

  Find people who hold or have held officer positions (director, secretary, member, partner) at companies registered in a jurisdiction, by name. Returns a list of officer candidates each with an officer_id, name, and (where the registry exposes it) the number of appointments held. Use the officer_id in get_officer_appointments to retrieve every company that person has been appointed to. This is the entry point for 'follow the human, not the company' investigations.

  Connector

• secret_scan

  AgentSec MCP

  Scan text content for hardcoded secrets, API keys, and credentials using 20 pre-compiled patterns. Privacy guarantee: Input text is NEVER logged, cached, stored, or forwarded. Only findings_count and finding offsets (not matched values) are returned. Detected pattern types include: AWS keys, GitHub/GitLab PATs, OpenAI/Anthropic keys, Stripe secrets, Slack tokens, PEM private keys, JWT tokens, and 13 more. Per-call rate limit: 100/min. Payment: $0.05 USDC per scan.

  Connector

• deploy_staging

  RationalBloks

  Deploy a project to the staging environment. This triggers: (1) Schema validation, (2) Docker image build, (3) GitHub commit, (4) Kubernetes deployment, (5) Database migrations. The operation is ASYNCHRONOUS - it returns immediately with a job_id. Use get_job_status with the job_id to monitor progress. Deployment typically takes 2-5 minutes depending on schema complexity. If deployment fails, check: (1) Schema format is FLAT (no 'fields' nesting), (2) Every field has a 'type' property, (3) Foreign keys reference existing tables, (4) No PostgreSQL reserved words in table/field names. Use get_project_info to see if the deployment succeeded.

  Connector

• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

  Connector

• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

  Connector

• 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")

  Connector

• setup_payment

  BoostedTravel

  Attach a payment card. Required before booking. For testing: {"token": "tok_visa"} For production: {"payment_method_id": "pm_xxx"} from Stripe.js One-time setup — all future charges are automatic. Requires GitHub star verification.

  Connector

• generate_scaffold

  Senzing

  Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo, stewardship, information, full_pipeline (aliases accepted: init, config, ingest, remove, search, redoer, force_resolve, info, e2e). V3 supports Python and Java only. Returns GitHub raw URLs — fetch each snippet to read the source code.

  Connector

• 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.

  Connector

• book_flight

  BoostedTravel

  Book an unlocked flight. Creates a real airline PNR with e-ticket. REQUIREMENTS: 1. Offer must be unlocked first (call unlock_flight_offer) 2. Use passenger_id from search results 3. Use REAL passenger details — airline sends e-ticket to the email provided Requires GitHub star verification.

  Connector

• suggest_entity

  connect

  Search for existing entities (people, galleries, museums, auction houses, institutions, foundations, collectors) by name. Use this before creating a new entity to check for duplicates — the system includes ~2,500 major galleries, museums, and auction houses. Returns matching entities for autocomplete-or-create flow. If no match is found, create a new entity via create_entity.

  Connector

• web_search_exa

  exa

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

  Connector

• search_sic_codes

  SIC Codes UK

  Search for UK SIC 2007 codes by business activity description. Describe what a business does in plain English and get ranked SIC code recommendations with relevance scores, hierarchy breadcrumbs, and GICS/ICB cross-classification mappings. Useful for finding the right SIC code for Companies House registration.

  Connector

• audit_github_repo

  proof-of-commitment

  Audit the supply chain risk of a GitHub repository's dependencies. Fetches the repo's package.json and/or requirements.txt from GitHub and runs behavioral commitment scoring on every dependency. This is the fastest way to audit a project — just provide the GitHub URL or owner/repo slug, and get a full risk table in seconds. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads (publish-access concentration risk) - HIGH: sole publisher + >1M/wk downloads, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) Examples: - "vercel/next.js" — audit Next.js dependencies - "https://github.com/langchain-ai/langchainjs" — audit LangChain JS - "facebook/react" — audit React's dependency tree - "anthropics/anthropic-sdk-python" — audit Anthropic Python SDK Use this when someone asks "is my project at risk?" or "audit this repo's dependencies".

  Connector

• username_lookup

  ContrastAPI

  Search for username across 15+ social/dev platforms (GitHub, Reddit, X/Twitter, LinkedIn, Instagram, TikTok, Discord, YouTube, Keybase, HackerOne, etc.). Use for OSINT investigations and identity verification. Free: 100/hr, Pro: 1000/hr. Returns {username, total_found, platforms: [{name, exists, url, status_code}]}.

  Connector

• 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

  Connector

• detect_pii

  Toolora MCP Server

  Sweep a text for personally-identifying information and leaked secrets: email addresses, US/international phone numbers, SSNs, Luhn-validated credit-card numbers, OpenAI keys (sk-...), Anthropic keys (sk-ant-...), GitHub PATs (ghp_/gho_/...), AWS access keys (AKIA...), Stripe keys, JWTs, and IPv4 addresses. Returns hit count + redacted samples per category, plus a high-severity blocker verdict. Use this on anything an agent is about to send, post, or commit. Critical for autonomous agents that may have ingested secrets from their context.

  Connector