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679,765 tools. Updated 2026-10-20 03:00

"Understanding Code Relationships and Dependencies" matching MCP tools:

  • Get all professional service relationships for an NZX company — auditors, law firms, share registrars, and bankers. Returns current and historical relationships, audit fee data, and companies sharing the same advisers. Useful for understanding corporate dependencies and hidden connections.
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  • Map the full dependency tree of an npm package and identify CRITICAL supply chain risks at every level. Unlike auditing a flat list of packages, this tool traverses the dependency graph — showing not just your direct dependencies but also what your dependencies depend on. Hidden CRITICAL packages (sole publisher + >10M weekly downloads) often lurk 1-2 levels deep. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads — sole point of failure for a massive attack surface - HIGH: sole publisher + >1M/wk, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) depth=1 (default): root package + all direct dependencies depth=2: also traverses one more level for any CRITICAL/HIGH direct deps (reveals hidden exposure) Examples: - audit_dependency_tree("express") — see all of Express's deps and their risk scores - audit_dependency_tree("langchain", 2) — reveal transitive CRITICAL deps 2 levels deep - audit_dependency_tree("@anthropic-ai/sdk") — audit Anthropic SDK full tree Use this when someone asks: - "What am I really depending on?" - "Are my dependencies' dependencies safe?" - "Show me the full supply chain risk for package X"
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  • Answer state and structure questions about ONE entity from the knowledge graph: current and past relations, dependencies, recent changes, evidence, contradictions and uncertainty. Suited to questions like "where does X work now?", "what does X depend on?" or "what changed for X this week?". Each relation carries ``estado`` (CURRENT | HISTORICAL | UNRESOLVED | UNKNOWN) and ``confianza`` (0-1). UNRESOLVED relations or open contradictions mean the current state is ambiguous. For topic-based questions across stored memories use cognitive_query. Args: subject: Entity name, alias or id. aspect: What to return: "current_state" (default) — current relations; legacy relations without a reliable date are listed under ``unknown``. "historical_state" — also relations that are no longer true. "contradictions" — open and resolved contradictions. "evidence" — relations with their evidence and whether each is justified. "relationships" — all incoming and outgoing relations, excluding the structural root link. "dependencies" — transitive current dependencies (depends_on, part_of, uses). "changes" — what started, ended, was learned late or was resolved within ``ventana_dias``. "uncertainty" — what is not known with confidence, with a reason. "all" — all of the above plus recent facts and episodes. at: Optional ISO date: answer as NEXUS knew it on that date, hiding what was not yet known or not yet true. depth: Hops of neighbors to include via current relations (0-2). ventana_dias: Window in days for "changes" (1-365, default 30). Returns data for the chosen aspect; ``truncated: true`` means the neighbor traversal hit its node limit.
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  • Check up to 50 packages at exact versions (for example from package.json, package-lock.json, requirements.txt, go.mod, pom.xml, Cargo.toml or a .csproj) against OSV.dev in one batch. Returns a summary count and only the packages with problems: malicious-package flags first, then vulnerabilities by severity with the version that fixes each and the minimum upgrade target. Use when the user pastes a dependency file or list, or asks to "audit my dependencies" or "check my package.json / requirements.txt", or which dependencies are vulnerable or outdated. Entries without an exact version are skipped and listed; transitive dependencies are only checked if included in the list.
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  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
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  • Discover correlations between different signal types. Example: relationship between ad fill rate and audience attention for QSR venues. Queries the cross_signal_insights table for pre-computed correlations, or computes ad-hoc correlations from the observation_stream when no pre-computed insight exists. WHEN TO USE: - Understanding relationships between different sensing signals - Finding which audience behaviors correlate with business outcomes - Discovering hidden patterns (e.g., crowd_energy vs purchase_intent) - Validating hypotheses about audience-venue-time relationships RETURNS: - data: Correlation analysis with: - signal_a, signal_b: The two signals being correlated - correlation_r: Pearson correlation coefficient (-1 to +1) - correlation_r2: R-squared (proportion of variance explained) - p_value: Statistical significance - sample_count: Number of data points used - effect_size: Cohen's d effect size - confidence_interval_lower, confidence_interval_upper: 95% CI bounds - insight_summary: Human-readable interpretation - metadata: { computation_method, window, filters_applied } - suggested_next_queries: Related correlation analyses to explore EXAMPLE: User: "Is there a correlation between audience attention and ad fill rate at QSR venues?" cross_signal_correlate({ signal_a: "attention_score", signal_b: "ad_fill_rate", filters: { venue_type: "restaurant_qsr" } }) User: "How does crowd energy relate to purchase intent during lunch hours?" cross_signal_correlate({ signal_a: "crowd_energy", signal_b: "purchase_intent", filters: { daypart: "lunch" } })
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  • List every error code in the Trillboards API error catalog. WHEN TO USE: - Understanding what error codes the API can return. - Building a client-side error handler that covers all cases. - Looking up error types, HTTP statuses, and documentation URLs. RETURNS: - object: "list" - data: Array of { code, type, http_status, description, doc_url } - total: Total number of error codes. Equivalent to GET /v1/errors but executed in-process (no HTTP round-trip). EXAMPLE: Agent: "What error codes can the API return?" list_error_codes()
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  • UNDERSTANDING — A VC firm's portfolio companies, each matched to the network and rated. Filter publishes_api=true (companies that actually ship an API — about 37% of any book), in_network=true, band, or min_score; sort by score (default), api_count, or name. The demand-side view of who a fund has backed. Understanding plan. Priced per result — $0.005 per request plus $0.0002 per record returned (less past 100), capped at $0.50 a request, under pay-as-you-go; included in Understanding and Influence. Estimate first at /api/v1/prices/estimate. See apis://prices.
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  • Check subscription status, plan details, billing cycle, and feature access. Useful for understanding what the business can and cannot do on their current plan.
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  • Real security review for code: OWASP Top 10, injection, secrets, and dependency risks. Cross-references imported dependencies against OSV.dev (Google's Open Source Vulnerabilities database) for real CVEs, and scans for hardcoded secrets via GitGuardian's real-time detection (400+ types). SPENDS your balance -- requires authentication (OAuth). Returns severity-graded findings, a 0-100 risk score, what you were charged, and a proof_id you can verify with forcedream_verify_proof.
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  • Answers a question by traversing the published knowledge graph and returning ranked reasoning paths instead of disconnected records. Each path is an ordered chain of relationships with a path score, a path confidence, the supporting evidence, the relationship types used and a plain-language explanation of every transition. Traversal respects relationship weight, evidence strength, concept ontology, semantic clusters and inverse relationships, and prunes weak branches automatically.
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  • List the user's categories (with item counts and parent relationships). Use the exact names to scope search's category filter.
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  • MITRE CWE detail by ID (format CWE-NNN or NNN). Returns name, abstraction, status, description, and parent/child CWE relationships.
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  • Inspect a Python package’s latest release, Python compatibility, declared dependencies, license metadata and PyPI-reported advisories. No code execution. Costs $0.003. Returns payment instructions for the Saylor endpoint; no provider account required.
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  • Return a single builder-facing overview of a project's capabilities: its tenant/data-sharing model (and what multiTenant enforces), every entity with its fields, the entity-to-entity relationships (reference fields), and which query parameters actually filter today. Call this to understand a project at a glance before writing app code, instead of piecing it together from list_entities + list_fields. For the full machine-readable REST contract, use generate_openapi_spec.
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  • Remove contacts from a contact list (list_id, or list_name as its name or slug). The contacts themselves are unchanged. Returns removed, not_member and not_found. Family follows relationships and is refused (code AUTO_SYNCED_LIST). undo_contact_change(change_id) puts them back. ($0.05; API key required)
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  • Returns The Code Score (security/code-quality/dependencies, 1000 points) for a project (aggregated) or a single vault. Provide exactly one of project_id or vault_id. Requires full data access (a paid plan; verification-only plans are not included). If the plan doesn't include Code Score access, or it hasn't been generated yet, returns the same response shape with empty sections/priorities rather than an error. 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.
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  • Should you depend on this open-source project? Repository report: adoption and maintenance (stars, forks, releases, commit activity, issues), license, known vulnerabilities in its dependencies (OSV), and an AI code review of the main entry file. Verdict adopt / trial / caution / avoid with a score and a PDF. If too few sources answer you are not charged (with async=true the core source is checked before the job is queued and charged). Costs $2 USDC per call (x402).
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  • Design an API stack — the best-rated catalog provider per capability, assembled into a stack. The Understanding preview is the top pick per capability; the full answer adds alternatives, per-pick artifact gaps, and an exportable APIs.json + Arazzo hint. Decompose the domain into capabilities first, then pass them here. Priced B2 (cross-catalog synthesis) — $0.05 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.
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  • Artist profile by MBID: type, country, life span, gender, area, aliases, tags/genres, release-groups, band-membership / collaboration relationships, and external links. Release-groups embed one upstream page (25); relationships are not capped. For the complete release-group list, call musicbrainz_browse_entities with target_type=release-group and link.artist.
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  • UNDERSTANDING — the evidence behind a capability. Every edge that lands on it: the provider, the tag, the exact OpenAPI file, a calibrated confidence, and the QUOTED FRAGMENT OF THE PROVIDER'S OWN CONTRACT that justifies the claim. Only edges at confidence >= 0.7 whose evidence was found verbatim in the source contract are published, so an edge here is checkable rather than asserted. This is what you cite when someone asks "says who?". Understanding plan. Priced B1 (single-entity synthesis) — $0.01 per call under pay-as-you-go; included in Understanding and Influence. See apis://prices.
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