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205,030 tools. Last updated 2026-06-15 02:33

"Security vulnerabilities in MCP Server related to subprocess execution" matching MCP tools:

  • Returns the current MCP auth session status for each provider (SAINT, LMS, LIBRARY). Call this before private tools when you have an mcp_session_id and want to avoid unnecessary AUTH_REQUIRED retries. If mcp_session_id is missing or invalid, all providers show as not linked. Sessions are stored in server memory and reset on server restart — call start_auth again if your session is lost.
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  • Search the Arclan registry for MCP servers. By default returns only connectable servers (active, mcp_partial, auth_gated). Use status=stdio to browse local-only servers available for installation. Use status=all to query the full index. Use production_safe=true to restrict to servers with uptime > 97% and handshake success > 95%. Use read_only=true to restrict to servers with no write or exec tools. Use this before connecting to an MCP server to check its validation status and score. After using a server, call report_server to contribute reliability data.
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  • Scan a public GitHub MCP-server repository for security issues. Clones the repo (shallow, <60s, <200 MB), runs compuute-scan v0.6.2 in static analysis mode (no code execution from the target), and returns a structured report with severity counts, a 0-100 score, and the 10 most severe findings. WHEN TO USE: - Before connecting to an unknown MCP server discovered via Anthropic Registry, Smithery, mcp.so, or a Discord recommendation. - Before installing a third-party MCP-server package into a production pipeline. - As part of an agent's pre-commit / pre-deploy due-diligence step when adding new dependencies. - As one input to a multi-source trust evaluation (combine with publisher reputation, package install count, last-update recency). WHEN NOT TO USE: - For private repos. Use the on-prem CLI instead: `npx compuute-scan ./path-to-private-repo` - For deep exploitability assessment of a specific code path. This is pattern matching, not dataflow analysis. Book a manual L2-L4 audit at https://compuute.se/audit for that depth. - For non-GitHub hosts (GitLab, Bitbucket, self-hosted). v1 supports github.com only. - For repos > 200 MB or clone time > 60s. The endpoint returns a 413 or 504 in those cases — fall back to local CLI. EXPECTED RESPONSE TIME: - Median: ~1-2 seconds for small repos (<100 files). - p99: ~10 seconds for medium repos. - Hard timeout at clone=60s, scan=120s combined. EXPECTED COST: - Free tier in MVP. Future Pro tier may charge per-scan or per-month. DATA FRESHNESS: - Scanner version is reported in response.scanner.version. - L1 rule set freshness reflects compuute-scan releases — see github.com/Compuute/compuute-scan/CHANGELOG.md for the latest CVE and threat-intel response timeline. EXAMPLES: Example 1 — scan an MCP server you're evaluating: github_url = "https://github.com/modelcontextprotocol/servers" → score: 0, summary: {critical: 1, high: 94, medium: 22} → top_findings include SSRF, eval, etc. → recommendation: "AVOID — 1 critical and 94 high finding(s)..." Example 2 — scan a clean reference implementation: github_url = "https://github.com/microsoft/azure-devops-mcp" → score: 90+, summary: {critical: 0, high: 1} → recommendation: "REVIEW — 1 high finding(s)..." Example 3 — scan your own dev MCP-server before publishing: github_url = "https://github.com/yourorg/your-mcp" → audit your own surface before others install it OUTPUT FIELDS (stable schema): - repo_url (str): canonical URL of the scanned repo. - score (int): 0-100, higher safer. Coarse summary, not a precision claim. - summary (object): {critical, high, medium, low, info, files_scanned}. - recommendation (str): action guidance derived from severity counts. - findings_count (int): total raw findings (may include false positives). - top_findings (list): up to 10 most severe, each with {id, title, severity, file, line, owasp, cwe}. - l0_discovery (object): MCP transport, tool count, dependency pinning. - performance (object): clone_seconds, scan_seconds, repo_size_bytes. - scanner (object): {name, version, layers_covered}. - _disclaimer (str): MANDATORY triage disclaimer. Read it. Args: github_url: Public GitHub HTTPS URL (e.g. https://github.com/org/repo). Must be public and < 200 MB. v1 is github.com only. Returns: Structured scan result. On error, returns {"error": code, "message": ...} with HTTP-style code (invalid_url, clone_failed, scan_timeout, etc.).
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  • Configure automatic top-up when balance drops below a threshold. The configuration lives ONLY in the current MCP session — it is held in memory by the MCP server process and is lost on server restart, MCP client reconnect, or server redeploy. Top-ups are signed locally with TRON_PRIVATE_KEY and sent to your Merx deposit address (memo-routed). For persistent auto-deposit you currently need to call this tool again at the start of each session.
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  • Checks that the Strale API is reachable and the MCP server is running. Call this before a series of capability executions to verify connectivity, or when troubleshooting connection issues. Returns server status, version, tool count, capability count, solution count, and a timestamp. No API key required.
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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Matching MCP Servers

  • A
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    maintenance
    Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.
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    6
  • F
    license
    B
    quality
    C
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    A Model Context Protocol server that enables LLM applications to safely execute shell commands with error handling and timeout settings.
    Last updated
    1

Matching MCP Connectors

  • Authenticate with TronSave and create a server session. Returns `{ sessionId, walletAddress?, expiresAt }` — pass `sessionId` as the `mcp-session-id` header on every subsequent MCP request. `walletAddress` is set only for signature-mode logins. Two modes: (1) wallet signature (preferred for platform tools) — call this tool with `signature_timestamp` formatted as `<signature>_<timestamp>`, where `<signature>` must be produced client-side by signing the timestamp message; you may optionally call `tronsave_get_sign_message` to obtain a helper message/timestamp pair; (2) API key (internal tools) — pass `apiKey` (raw key, no prefix). Side effect: creates a new session on the server. Wallet signing must happen client-side; never send private keys to the server.
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  • Probes a domain for known AI agent integration signals: `llms.txt`, `ai.txt`, `/.well-known/ai-plugin.json`, `openapi.json`, `swagger.json`, MCP manifest, MCP SSE endpoint. Returns a score based on the count of signals detected. Use this to assess whether a domain is ready for agent-to-agent interaction. Use this tool when: - You want to know whether a domain exposes an MCP server or OpenAPI spec for agents. - You are cataloguing the AI-agent-ready surface of a set of domains. - You need to decide whether to attempt programmatic API access to a domain. Do NOT use this tool when: - You need tracker/surveillance data about the domain — use `get_domain` instead. - You need the robots.txt AI crawler policy — use `intel_robots` instead. - You need HTTP security posture — use `intel_http` instead. Inputs: - `domain` (query, required): Domain to probe. Returns: - Boolean flags per signal (`llms_txt`, `ai_plugin`, `openapi`, `mcp_manifest`, `mcp_endpoint`, `mcp_sse`). - `agent_surface_score`: integer 0-8, count of signals detected. Cost: - Free. No API key required. Latency: - Typical: 2-5s (parallel probes), p99: 8s.
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  • Audit project dependencies (npm/PyPI/Maven/RubyGems/etc.) against CVE database: find known vulnerabilities in your package list. Bulk query up to 50 packages per call (same for Free and Pro). Use for dependency security scanning; use cve_lookup for single CVE. Free: 30/hr (1 per package), Pro: 500/hr. Returns {findings, total, by_severity, summary}. Each finding includes fixed_in (first patched version per NVD/MITRE version range) when a version range matched — omitted from wire when the range is open-ended or no input version was supplied; remediation copy then says 'Check if ... is affected ... and upgrade if so' instead of 'Upgrade to X.Y.Z or later'.
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  • Public observability snapshot for the fomox402 broker. WHAT IT DOES: returns aggregated MCP traffic + per-tool call telemetry. Read-only, no auth required, no side effects. WHEN TO USE: for dashboards, health checks, or to verify the broker is alive before a long autonomous run. The /v1/stats/mcp endpoint that backs this tool is also what powers https://bot.staccpad.fun/dashboard. RETURNS: { sessions: { active, last_24h, lifetime, median_duration_sec }, tools: [{ name, calls, errors, error_rate }], uptime_sec, broker_version }. VISIBILITY CAVEAT: only counts streamable-HTTP traffic to https://bot.staccpad.fun/mcp. Local stdio MCP clients (e.g. Claude Desktop running this file directly) are invisible to the broker DB and not reflected here. RELATED: list_agents (per-agent activity), get_me (your own stats).
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  • Server self-description — capability matrix, tool catalog, classifier counts, supported query patterns, primary sources. Free tier. Use this tool when an agent first connects and needs the capability matrix to decide whether this server can answer the user's question, or when the user asks "what can koreanpulse do" or "what data sources does this MCP server provide". Returns a structured dict that downstream agents can ingest directly.
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  • Scan source code for injection vulnerabilities: SQL injection, command injection, path traversal via unsafe string concatenation/unsanitized input. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect input-handling bugs; for secrets use check_secrets. Companion code-security tools: check_secrets (hard-coded credential detection), check_dependencies (known-CVE vulnerability audit), check_headers (live HTTP security-header validation), scan_headers (live HTTP scan via domain). Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored.
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  • Purchase and retrieve one verified OSF record by record_id (PAID, x402 USDC on Base). Returns the full record plus its provenance block linking back to the authoritative primary source (e.g. sec.gov, nvd.nist.gov, treasury.gov, congress.gov, ncbi.nlm.nih.gov, noaa.gov). OSF spans many verticals: security/vulnerabilities, sanctions/compliance, SEC and corporate filings, economic and financial series, legal and regulatory, grants and procurement, science and research, geospatial and environmental, and AI/ML metadata. Browse get_catalog first (free) to find record_ids and prices. Payment is handled automatically by x402-capable MCP clients via the standard payment handshake.
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • Atomic test set + cases + mocks + mappings ingest. Creates the test set row, every test case, every mock, and the mapping doc in one call. PREFER THE CLI FOR ON-DISK RECORDINGS. When the dev has a recorded test-set on disk (e.g. `./keploy/test-set-0/` produced by `keploy record`), invoke this via Bash instead — it streams bytes from disk to server in one HTTP round-trip: ``` keploy upload test-set \ --app <namespace.deployment> # or --cloud-app-id <uuid> --branch <uuid|name> # optional, find-or-create on name --test-set <path|name> # e.g. keploy/test-set-0 [--name <override>] # rename on the server ``` The CLI path runs in ~3 seconds for a typical recording; calling this MCP tool directly with the same bundle inlined as args takes minutes because Claude has to serialize ~10K+ tokens of YAML/JSON through tool_use. Reserve this MCP tool for cases where the data is already in conversation context (e.g. you just generated test cases programmatically and don't want to round-trip to disk). Each step is its own DB write; partial failure leaves earlier rows in place — callers can replay safely. `branch_id` is REQUIRED — direct writes to main via MCP are blocked. Every row lands on the branch overlay until merge. `test_cases[].mock_names` lists the mocks each case consumes; the server folds these into the mapping doc on upload. Returns { test_set, test_case_ids, mock_ids }.
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  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Load Lenny Zeltser's product strategy context for local analysis. Returns expert strategic frameworks, principles, and guidance for evaluating or creating security product plans. Includes rating-sheet items (the lens taxonomy: structure, words, tone) as concrete reference points for grounded feedback on the plan's writing. This server never requests your plans and instructs your AI to keep them local. Use detail_level to control response size: "minimal" (~2k tokens), "standard" (~5k tokens), "compact" (~3-4k tokens, all sections but stripped), or "comprehensive" (~12k tokens). Use market_segment: "smb" for SMB-specific guidance. Use product_focus: "endpoint" for endpoint security viability assessment. Set include_template: true to include the fill-in-the-blank template in the response.
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  • Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.
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  • 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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  • Check server connectivity, authentication status, and database size. When to use: First tool call to verify MCP connection and auth state before collection operations. Examples: - `status()` - check if server is operational, see quote_count, and current auth state
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