DESTRUCTIVE: Permanently delete an app, its Docker service, volume, and all data including version history. This cannot be undone. You MUST confirm with the user before calling this tool.
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127,292 tools. Last updated 2026-05-05 13:25
"Analyzing Python Modules, Docker Files, and Generating Mock Data or Outputs" matching MCP tools:
- Runs a single end-to-end execution of an existing automation against a mock conversation, returning success/failure plus the channel target and duration. Mirrors a real production firing. Behavior: - Sends REAL messages by default: posts the configured webhook, sends the configured email, posts the Slack message, or writes the HubSpot record. Use override_email (email channels) or override_webhook (webhook channels) to redirect delivery to a safe test target. - Each call fires another real delivery. - Errors when the perspective or automation is not found, or you do not have access. Webhook URLs (configured or override) are validated. - Mock conversation defaults: trust score 85, status complete, "Test Participant" / test@example.com. Override participant_name, summary, and tags via test_data. - Returns success: true also when the automation's condition skips delivery (e.g., tag/trust filter doesn't match the mock). The error field is populated only on real delivery failures. When to use this tool: - Verifying a freshly-created automation actually delivers before relying on it. PREFER override_email/override_webhook to avoid spamming real recipients. - Reproducing a delivery failure surfaced in automation_list (last_error). When NOT to use this tool: - Listing what's configured — use automation_list. - Changing config — use automation_update. - Removing the automation — use automation_delete.Connector
- Create a mock user. Data is not persisted — returns a fresh fake user echoing your inputs.Connector
- 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
- Get code from a remote public git repository — either a specific function/class by name, a line range, or a full file. PREFERRED WORKFLOW: When search results or findings have already identified a specific function, method, or class, use symbol_name to extract just that declaration. This avoids fetching entire files and keeps context focused. Only fetch full files when you need a broad understanding of a file you haven't seen before. For supported languages (Go, Python, TypeScript, JavaScript, Java, C, C++, C#, Kotlin, Swift, Rust) the response includes a symbols list of declarations with line ranges. This is not a first-call tool — use code_analyze or code_search first to identify targets, then extract precisely what you need.Connector
- Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. Indexes only source code files (.py, .java, .cs, .rs) and READMEs — NOT build files (Cargo.toml, pom.xml), data files (.jsonl, .csv), or project configuration. For sample data, use get_sample_data instead. Covers Python, Java, C#, and Rust SDK usage patterns including initialization, record ingestion, entity search, redo processing, and configuration. Also includes message queue consumers, REST API examples, and performance testing. Supports three modes: (1) Search: query for examples across all repos, (2) File listing: set repo and list_files=true to see all indexed source files in a repo, (3) File retrieval: set repo and file_path to get full source code. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval — fetch to read the source code.Connector
Matching MCP Servers
- AlicenseBqualityCmaintenanceA mock MCP server for testing MCP client implementations and development workflows. Supports tools, prompts, and resources across multiple transport protocols (stdio, HTTP, SSE).Last updated1MIT
- Alicense-qualityCmaintenanceEnables AI agents to safely explore directories, read files, search content by pattern or filename, and edit files with checksum verification and dry-run preview within sandboxed filesystem access.Last updated170ISC
Matching MCP Connectors
Read-only PostgreSQL, MySQL, SQL Server access via MCP — 24 dialect-aware hosted tools.
A simple MCP server built with FastMCP and python
- INSPECTION: Retrieve Terraform outputs from a completed deployment Returns structured output values (VPC IDs, endpoints, cluster names, etc.) after a successful deploy. Sensitive outputs are redacted (shown as '(sensitive)'). By default returns outputs for the latest successful deploy. Optionally specify job_id to get outputs for a specific deployment. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id (specific deployment), lifecycle (filter by step e.g. 'cloud-provision').Connector
- Return a compact titles-only tree of the course: course → modules → lessons. Ideal for agents to plan reorders, spot empty lessons, or summarize a course. Does NOT include lesson body content.Connector
- Read the contents of an attached file directly. Use this when the user asks 'what is in this file?' or 'read this document'. Works for text files (.txt, .md, .json, code files, etc.) and PDFs (returns OCR-extracted text after files.ingest). For images, use files.get_base64.Connector
- 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
- Edit a file in the solution's GitHub repo and commit. Two modes: 1. FULL FILE: provide `content` — replaces entire file (good for new files or small files) 2. SEARCH/REPLACE: provide `search` + `replace` — surgical edit without sending full file (preferred for large files like server.js) Always use search/replace for large files (>5KB). Always read the file first with ateam_github_read to get the exact text to search for.Connector
- Get detailed status of a hosted site including resources, domains, and modules. Requires: API key with read scope. Args: slug: Site identifier (the slug chosen during checkout) Returns: {"slug": "my-site", "plan": "site_starter", "status": "active", "domains": ["my-site.borealhost.ai"], "modules": {...}, "resources": {"memory_mb": 512, "cpu_cores": 1, "disk_gb": 10}, "created_at": "iso8601"} Errors: NOT_FOUND: Unknown slug or not owned by this accountConnector
- Creates a code vault and queues the initial analysis. IMPORTANT: Always use LOCAL_AGENT (or AGENT) unless the user explicitly requests remote analysis or Docker is unavailable. LOCAL_AGENT runs locally via Docker; source code stays on the machine and only anonymous analysis data is uploaded. A Git repo is only required if you want Git-based insights (git-history, code-contributors). If Git insights are needed, the mounted path must be a standard Git repo containing a .git directory (not a .git file pointing to a worktree). The response includes next_steps.commands that must be executed to start the local agent. Use GIT/FILE_ARCHIVE only when the user provides a reachable URL plus read credentials (username/password or token). Cold starts can cause the first request to time out; retry with backoff. Requires X-API-Key (existing users can generate an API key in the web app). If headers aren't supported, pass api_key in arguments.Connector
- Get Secureship API authentication instructions. Call this FIRST before generating any code examples with authentication headers. Secureship uses X-API-KEY header authentication, NOT Bearer tokens.Connector
- Get detailed info for a single lending pool including APY history over time. Useful for analyzing rate trends and comparing pools. Use read_pool_list to discover pool addresses.Connector
- List AI modules and their enabled/disabled state for a site. Also returns the list of modules available for the site's plan. Requires: API key with read scope. Args: slug: Site identifier Returns: {"modules": {"chatbot": true, "seo": false, "translation": false, "content": false}, "available": ["chatbot", "seo", "translation", "content"]} Errors: NOT_FOUND: Unknown slugConnector
- Crop transparent edges from one or more PNG files. Single file returns PNG; multiple files return a ZIP.Connector
- Returns this server's runtime configuration: upload endpoint URL, output file TTL, file size limits, and base64 encoding rules. Call this before working with large files (≥ 4 MB) or when building multi-step workflows that chain tool outputs.Connector
- Download one or more files server-side and return their content as base64-encoded strings. Use this to inspect images, PDFs, or any binary file attached to messages when you cannot access presigned S3 URLs directly. Supports up to 5 files per call, max 15 MB each. For large files batch in groups of 1-2 to avoid oversized responses.Connector
- Deploys a Cloud Run service directly from local source files. This method is suitable for scripting languages like Python and Node.js, of which the source code can be embedded in the request. This is ideal for quick tests and development feedback loops. You must include all necessary dependencies within the source files because it skips the build step for faster deployment. **Key Requirements:** 1. source_code: Should set to sourceCode.inlinedSource.sources with array of source files, each having `filename` and `content`. 2. Size limit: you are subject to total request size limit of 50MiB.Connector