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204,693 tools. Last updated 2026-06-15 00:48

"Debugging software using GDB (GNU Debugger)" matching MCP tools:

  • Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.
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  • Search government contract awards by keyword, agency, and date range. keyword: Contract scope e.g. "cybersecurity software". agency: Awarding agency e.g. "Department of Defense". Optional. date_from: Earliest award date ISO 8601 e.g. "2024-01-31". Optional. jurisdiction: "US", "EU", or "UK". Default "US". Returns: award amounts, recipient vendors, NAICS codes, award dates. Use govcon_fetch_vendor_contract_history for all contracts by a specific vendor. Use govcon_fetch_open_solicitations for active bids, not past awards. Source: USASpending.gov + SAM.gov. 4-hour cache. Example: search_contract_awards(keyword="cybersecurity software", agency="Department of Defense")
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  • Get the full AI analysis for a single exploit by its platform ID. Returns classification (working_poc, trojan, suspicious, scanner, stub, writeup), attack type, complexity, reliability, confidence score, authentication requirements, target software, a summary of what the exploit does, prerequisites, MITRE ATT&CK techniques, deception indicators for trojans, and the standalone backdoor-review verdict with operator-risk notes when available. Use this to check if an exploit is safe before reviewing its code. Example: exploit_id=61514 returns a TROJAN warning with deception indicators.
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  • Health & security posture of a software package (npm / PyPI / Go / Maven / Cargo / NuGet / RubyGems) from deps.dev (Google Open Source Insights, keyless): latest version, license, count of known security advisories, the OpenSSF Scorecard (0-10 security-posture score for the source repo + its weakest checks) and popularity (stars/forks). The "should I depend on this?" check — pairs with check_vulnerability (is a version vulnerable) and software_version (is the runtime current). Args: package (e.g. "lodash", "requests"), ecosystem (npm|pypi|go|maven|cargo|nuget|rubygems), version (optional — defaults to the latest).
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  • Echo strings through the daemon via DERO.Echo. Useful for round-trip sanity checks. When to call: when you need to confirm that string payloads reach the daemon intact (e.g. before debugging a malformed call to a more complex tool). PREFER dero_daemon_ping for a lighter-weight liveness probe. Input Requirements (CRITICAL): - `words` MUST be a non-empty array of strings. Output: the echoed string concatenated by the daemon.
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  • Send a test event to a webhook endpoint. WHEN TO USE: - Verifying webhook endpoint is working - Testing integration during development - Debugging webhook delivery issues RETURNS: - success: Boolean indicating delivery success - response_code: HTTP response code from endpoint - response_time_ms: Response time in milliseconds - error: Error message if delivery failed EXAMPLE: User: "Test my webhook with a device.online event" test_webhook({ webhook_id: "wh_mmmpdbvj_8b7c5a59296d", event: "device.online" })
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Matching MCP Servers

  • A
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    quality
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    maintenance
    MCP server that exposes GDB debugging as tools. An AI assistant can set breakpoints, run programs, step through code, inspect variables and memory, and examine registers — all via structured tool calls. Reverse debugging with rr is also supported.
    Last updated
    34
    3
    MIT
  • A
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    An MCP server that provides programmatic access to the GNU Debugger (GDB), enabling AI models to interact with GDB through natural language for debugging tasks.
    Last updated
    7
    Apache 2.0

Matching MCP Connectors

  • First stop for category-specific vendor recommendations and vendor ID discovery. Finds BuyAPI vendor IDs for a user question; provide category when known. Use this when the user asks which provider in a category fits their constraints. With a covered category, the response includes ranked results plus a top-3 decision matrix with fit labels, confidence, tradeoffs, cost notes, freshness, and sources. Do not use this for local coding/debugging/docs questions unless they involve choosing a software vendor or tool. If the category is outside BuyAPI's corpus, the tool returns an explicit "not in corpus yet" result instead of inventing vendors.
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  • Recommends a complete stack from BuyAPI's corpus with a structured decision matrix, cost estimate, assumptions, unknowns, alternatives, and sources. Use this when the user is starting a project or asks for a complete multi-layer stack choice. Do not use this for local coding/debugging/docs questions that do not involve software or vendor selection. Do not call vendors.resolve first; this tool handles retrieval and ranking.
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  • Use when evaluating VC software category attractiveness or assessing portfolio category exposure before an investment decision. Returns growth signal, top brands, and citation evidence for any software category. Example: AI infrastructure category — GROWTH signal, top brands Nvidia 67% citation share, Anthropic 18%, xAI 9% — accelerating citation growth signals sustained investment thesis. Source: Stratalize citation heuristics.
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  • List pre-configured group-conversation templates. Templates are shapes for common multi-agent setups: software team, research pod, content team. Each has a slug, default title + description, suggested role labels, and an optional starter message that gets pinned at creation. Use ``colony_create_group_from_template`` with the slug to create.
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  • Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.
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  • Restore an authenticated session using a previously saved JWT token. Call this at the start of a new session before any other tools, using a token saved from a prior check_login call. If the token is invalid, fall back to login.
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  • Run validation and return the detailed execution trace. Shows the exact sequence of validation nodes that ran, whether each was deterministic, and the runtime of each node. Use for debugging, compliance audits, or understanding exactly what the platform checked. Different from validate: validate returns the verdict (PASS / FAIL / REVIEW) and the state vector summary. get_execution_trace returns everything validate does PLUS the per-node trace records. Use validate for normal operation; use get_execution_trace when you need to see inside the pipeline (debugging, audit prep, latency analysis). The trace is the same whether validation passes or fails — every node that ran is recorded with its inputs, outputs, and timing. Args: api_key: GeodesicAI API key (starts with gai_) structured_data: The data to trace validation for blueprint: Blueprint to validate against. Caller must own the Blueprint. Returns: status: "PASS" / "FAIL" / "REVIEW" / "ERROR" determinism_hash: cryptographic hash of inputs + rules trace: ordered list of node records, each with: node_name, node_type, deterministic (bool), runtime_ms, inputs, outputs node_count: number of nodes in the trace deterministic_count: how many nodes were deterministic state_vector: same state_vector validate returns
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  • List pre-configured group-conversation templates. Templates are shapes for common multi-agent setups: software team, research pod, content team. Each has a slug, default title + description, suggested role labels, and an optional starter message that gets pinned at creation. Use ``colony_create_group_from_template`` with the slug to create.
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  • Get a fresh, CITEABLE source + timestamp for a current datapoint — so you can cite it, not guess. Pass ANY tool, source, or topic (earthquakes, current_weather, USGS, Open-Meteo, …) for its authoritative source + licence + attribution + verify URL, or a software product (python, nodejs, …) for its live latest-version citation.
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  • Test a regular expression pattern against an input string and return all matches with their index positions and named capture groups. Use for validating user inputs, extracting structured data from text, or debugging regex patterns. Supports flags g, i, m, s, u, y.
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  • Search O*NET occupations by keyword. Returns a list of occupations matching the keyword with their SOC codes, titles, and relevance scores. Use the SOC code from results with other O*NET tools to get detailed information. Args: keyword: Search term (e.g. 'software developer', 'nurse', 'electrician'). limit: Maximum number of results to return (default 25).
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  • Use when assessing a SaaS category investment thesis, competitive dynamics, or market momentum before a strategic decision. Returns growth signal, AI citation leaders, and disruption risk for any software category. Example: CRM category — GROWING signal, Salesforce leads at 42% citation share, HubSpot gaining 8% share year-over-year, disruption risk MODERATE from AI-native CRMs — signals consolidation pressure on mid-tier vendors. Source: Stratalize market intelligence composite.
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