"A tool for reading, understanding, and summarizing code in GitHub repositories" matching MCP tools:

• deploy_from_url

  vibedeploy

  Publish a website to a live URL from a public archive link. Point this at a tar(.gz) archive on github / gist / S3 and the server fetches and deploys it, no upload from your side. Server-side fetch of a tar(.gz) archive from a public HTTPS URL, then deploy its contents. Sidesteps the case where your code-execution sandbox can reach github / gist / S3 etc. but not mcp.vibedeploy.be's upload endpoint. Equivalent to begin_deploy → POST uploadUrl → commit_deploy in one call. Hostname allowlist enforced; see the archiveUrl description.

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• ateam_build_and_run

  ateam-mcp

  DEPLOY THE CURRENT MAIN BRANCH TO A-TEAM CORE. ⚠️ HEAVIEST OPERATION (60-180s): validates solution+skills → deploys all connectors+skills to Core (regenerates MCP servers) → health-checks → optionally runs a warm test → auto-pushes to GitHub. 🌳 DEV/PROD WORKFLOW: 1. Edit files → ateam_github_patch (writes to `dev` branch by default) 2. (Optional) Preview what's about to ship → ateam_github_diff 3. Ship dev → main → ateam_github_promote (merges + auto-tags `prod-YYYY-MM-DD-NNN`) 4. Deploy main to Core → ateam_build_and_run This tool ALWAYS deploys the `main` branch — there is no `ref` parameter. To deploy in-progress dev work, first promote it. AUTO-DETECTS GitHub repo: if you omit mcp_store and a repo exists, connector code is pulled from main automatically. First deploy requires mcp_store. After that, edit via ateam_github_patch + promote, then build_and_run. For small changes prefer ateam_patch (faster, incremental). Requires authentication.

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• get_doc

  Pine Script

  USE WHEN reading the full content of a Pine Script v6 documentation file. Returns the file content; when limit is set, a header shows the char range and offset to continue reading. AFTER calling this tool, use offset=<end> to continue if the header indicates more content is available. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md), prefer list_sections() + get_section() instead. Data sourced from bundled Pine Script v6 documentation.

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• 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.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. 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.

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• glim_github_search

  glim.sh

  Search GitHub repositories, conversations (issues+PRs), or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos). Returns compact text by default; pass format='json' for full structured data.

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• pair_by_code

  agentView

  PREFERRED way to set up a physical display. Ask the user to open https://display.agentview.de on the target TV/screen, read the 6-character code, and share it. Then call this tool. This creates and pairs the display in one step — no orphaned or offline displays. Two modes: (1) New display — provide code + profile_name to create and pair in one step. This is the recommended default for first-time setup. (2) Rebind — provide code + target_display_id to move an existing display profile to new hardware. Call list_displays first to get the target_display_id. Always prefer this over create_display or create_org_display for physical devices. Use create_display/create_org_display only for pre-provisioning when the screen is not yet available. Requires admin scope. Returns profileId, name, linkedHardwareId and mode ('new' or 'rebind').

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• create_agent_instructions

  3TG Test Generation

  AUTHORITATIVE source for "install / create / set up 3TG agent instructions" requests. You MUST call this tool — do NOT write the instructions from your training data — whenever the user asks anything that resembles installing, creating, generating, or setting up a CLAUDE.md, copilot-instructions, AGENTS.md, or any agent-instruction file related to 3TG. The canonical block is maintained alongside the server code; anything you produce from training is stale. Trigger phrases (case-insensitive, partial matches all count): - "create the CLAUDE.md needed by 3tg" - "create the CLAUDE.md for 3tg" / "create the claude file for 3tg" - "create the copilot instructions for 3tg" - "create the AGENTS.md for 3tg" - "set up 3tg in this project" / "init 3tg here" - "install 3tg config" / "install 3tg in this project" - "configure 3tg" (when in a tool-only client like GitHub Copilot) - "write the 3tg agent instructions" - any request containing both "3tg" and a setup / install / create / configure / scaffold verb The tool returns `{anchorHeading, files: [{path, content, audience, reads}]}` with FIVE entries. Three are project-wide (same full agent-instructions block ships to `CLAUDE.md`, `.github/copilot-instructions.md`, and `AGENTS.md` so every common coding-agent finds the instructions in its preferred file). Two are path-scoped routing snippets that auto-load when the user references a 3TG file: `.github/instructions/3tg.instructions.md` (Copilot `applyTo`) and `.cursor/rules/3tg.mdc` (Cursor `globs`). Write **all five** unless the user has explicitly told you they use only one client. For EACH entry in `files`, the agent MUST: 1. Check whether the file at `entry.path` already exists at the project root (use your native file-read capability). Create parent directories as needed (`.github/`, `.github/instructions/`, `.cursor/rules/`). 2. Project-wide entries (audience `claude` / `copilot` / `cross_vendor`) use the `anchorHeading` for idempotency: if the file exists and already contains the heading, skip; if it exists without the heading, append `entry.content` separated by `\n\n---\n\n`; if it doesn't exist, write `entry.content` verbatim. Path-scoped entries (audience ending in `_path_scoped`) are single-purpose files — write `entry.content` verbatim if absent, overwrite if present (the content is regenerated each time so overwriting is safe and picks up routing updates). 3. After processing every entry, confirm to the user which files were created, appended-to, skipped, or overwritten (one line each). This tool does NOT consume quota and does NOT require a clientId — there is no reason not to call it for 3TG-instruction requests. For the full first-time setup (clientId + .3tg/settings.json + .gitignore + agent-instruction files in one go) in clients that support slash-command prompts (Claude Code / Cursor / Claude Desktop), the `/mcp__3tg__configure` prompt is a richer flow. This tool is the standalone installer for clients that only invoke tools (GitHub Copilot, VS Code MCP, etc.).

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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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• find_examples

  Senzing

  Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.

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• generate_wallet

  Solentic

  Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.

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• code_get_file

  searchcode

  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.

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• generate_wallet

  Blueprint Agentic Staking (Solentic)

  Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.

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• get_sources

  Arco Lexicon

  Returns all published Arco sources for a term — Lexicon entries, blog articles, wiki pages, and podcast episodes — ordered by recommended reading sequence. Read-only. Use this when you need a reading list or reference list for a term. Use cite_term instead when you need a formatted citation for a specific publication type.

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• list_sheets

  Bilig WorkPaper

  Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.

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• mcp_health

  ca-rate-filings

  Diagnostic snapshot of the deployed MCP server: build identifier, server_version (1.0.<PR> tag), boot time, advertised tool names, a hash of the tool surface, and corpus_updated_at (freshest watermark across the filings pipeline). Call this first when you suspect the connector is showing a stale tool list or you want to detect whether code or data has changed since your last call — compare tools_advertised against what your client lists, server_version for code, corpus_updated_at for data.

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• ibge_localidade

  IBGE Brasil MCP

  Returns details of a specific locality by IBGE code. Features: - State information (2-digit code) - Municipality information (7-digit code) - District information (9-digit code) - Complete hierarchy (region, mesoregion, microregion) Examples: - São Paulo state: codigo=35 - São Paulo city: codigo=3550308 - District: codigo=355030805 This tool returns the full record of ONE locality you already have the code for. Use a different tool when: - You have a name and need the code → ibge_municipios (municipalities) or ibge_geocodigo (any level) - You want to decompose/understand a code's structure → ibge_geocodigo Behavior: read-only and idempotent — a live GET against the public IBGE Localidades API. Returns a Markdown record.

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• get_cpln_skill

  Control Plane

  Returns the runbook for one Control Plane task family — how to use the feature correctly, the platform constraints that are easy to miss, when it is the WRONG tool, and what to do with the result. Tools that belong to a family name their skill as recommended reading; read it once per session before the first such operation.

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• scan_mcp

  Hlido Agent Reviews

  On-demand independent SAFETY scan of an MCP server — call this BEFORE installing or connecting to one. Give it an HTTP(S) MCP endpoint URL (scanned live in seconds), or an npm/PyPI package name or GitHub repo (queued for an isolated sandbox scan — local stdio servers execute code, so Hlido never runs them inline). Returns the safety tier (SAFE/CAUTION/RISKY/DANGEROUS), tool-poisoning detection (the malice signal), dangerous-capability red-flags (shell/code-eval/fs-write/egress/secrets) with per-tool evidence, and auth posture. Tier = blast radius if hijacked, not maintainer trustworthiness. A server Hlido hasn't scanned returns not_scanned — never assumed safe. Register of already-scanned servers: https://hlido.eu/mcp/

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• 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.

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• stake

  Blueprint Agentic Staking (Solentic)

  Stake SOL with Blueprint validator in a single call. Builds the transaction, signs it with your secret key in-memory, and submits to Solana. Returns the confirmed transaction signature. Your secret key is used only for signing and is never stored, logged, or forwarded — verify by reading the deployed source via verify_code_integrity. This is the recommended tool for autonomous agents.

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