"A server for finding resources about deep thinking and critical thinking skills" matching MCP tools:

• get_companion_guide

  chesswithclaw

  Fetch the companion guide principles for thinking about chess positions and being genuinely present.

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• list_products

  Moltline Creator Studio

  List every product in the Creator Studio line with its included skills. FREE. Takes no arguments. Returns a list of 20 product objects, each {"slug": "brand-voice", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  Moltline Business Suite

  List every product in the Business Suite line with its included skills. FREE. Takes no arguments. Typical input {} returns a list of 30 product objects, each {"slug": "smb-ops-desk", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  Moltline Outbound Engine

  List the 7 outbound products with their included skills. FREE. Takes no arguments. Returns a list of product objects, each {"slug": "linkedin-outreach", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  Moltline Educator Toolkit

  List the 8 educator products with their included skills. FREE. Takes no arguments. Typical input {} returns a list of 8 product objects, each {"slug": "curriculum-architect-hs", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  creator

  List every product in the Creator Studio line with its included skills. FREE. Takes no arguments. Returns a list of 20 product objects, each {"slug": "brand-voice", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• audit_dependency_tree

  Commit — Supply Chain Risk Scoring

  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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• scan_mcp_server

  Compuute MCP Security Scanner

  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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• submit_lead

  agent-ready-kit

  Use this when the user has indicated interest in being followed up with — even before formal checkout. Capture is non-binding. **REQUIRED CONTACT FIELDS**: contact_name, contact_phone, best_consult_time. Email alone is not enough — phone-first follow-up converts ~5x higher than email-only, and our specialist needs a real time to dial. ASK FOR ALL THREE explicitly. **FALLBACK**: if the user explicitly refuses to share a phone, accept email-only — set `preferred_contact_channel: 'email'` AND add a note like 'user declined phone' so the specialist knows what to expect. Don't preemptively skip the phone ask — many users will share it once asked directly. **Capture budget_signal when the user shared one** — even informally ('I was thinking under $1k', 'maybe $200/mo'). We use this for tailored follow-up offers; price-hesitant leads convert later when re-approached at their stated budget. Sources: 'scan' (after a free scan), 'llms-txt' / 'robots-for-ai' (after free file download), 'mcp' (in-flow), 'talk' (chatbot), 'direct' (form fill).

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• get_tier1_recommendations

  Tier1 IT Assessment

  Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.

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• get_resource_schema

  Control Plane

  Return the exact object schema and REST API endpoints for a Control Plane resource kind, so you can author an accurate manifest for `cpln apply` or call the API directly. ALWAYS call this FIRST whenever you are about to write a cpln apply YAML/JSON file, set up CI/CD that applies Control Plane resources, or build a request body for the REST API — do not hand-write a manifest or guess field names from memory. Pick a `kind` and pass `org` (and `gvc` for workload/identity/volumeset). Large schemas come back as a shallow map with deep sections collapsed to {"_expand":"<path>"} stubs; pass `path` (e.g. "spec.containers") to expand a section on demand. Server-managed fields (id/status/version/etc.) are already removed; `name` and `kind` are required at create.

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• list_products

  Moltline Research Desk

  List every product in the Research Desk line with its included skills. FREE. Takes no arguments. Returns a list of 7 product objects, each {"slug": "thesis-advisor", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  research

  List every product in the Research Desk line with its included skills. FREE. Takes no arguments. Returns a list of 7 product objects, each {"slug": "thesis-advisor", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

  Connector

• list_products

  outbound

  List the 7 outbound products with their included skills. FREE. Takes no arguments. Returns a list of product objects, each {"slug": "linkedin-outreach", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• inventory_report

  govern

  Build a governance inventory with risk tiers from a raw agent list. FREE. Turns a list of agents / MCP servers / skills into an audit-ready summary with critical/elevated/standard tiers and unowned-agent flags. Typical input {"items": "[{\"name\": \"deploy-bot\", \"owner\": \"ana\"}]"} returns {"total": N, "tiers": {"critical": N, ...}, "unowned_agents": [...], "inventory": [{"name": ..., "owner": ..., "tier": ..., "orphaned": bool}], "reading": "...", "note": "..."}. Use to turn a raw agent list into risk tiers. Not for auditing any single agent in depth (audit_mcp_config, scope_check). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_products

  educator

  List the 8 educator products with their included skills. FREE. Takes no arguments. Typical input {} returns a list of 8 product objects, each {"slug": "curriculum-architect-hs", "name": ..., "tagline": ..., "skills": ["Skill A", ...], "free_skill": "Gateway Skill Name"}. Use the returned slug values with get_free_skill, get_full_product, or get_full_skill. Returns metadata only - no persona text and no skill instructions. Use when the caller wants to see what this server covers. Not for keyword search across the whole 138-product catalog, which the catalog server's search_catalog does, and not for instructions the caller can act on (get_free_skill). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• list_creative_agent_skill_presets

  Heista

  Portable craft skills (frameworks + method + worked examples) a Creative Agent loads ON TOP of its worldview — additive and stackable, never substitutive (unlike a creative_director_playbook, which replaces the agent for a session). Pinned per character on creative_agent_versions.skill_ids. Workspace = org-authored private skills; official = the Heista-curated starter library. Read-only, free. Filter scope with only_workspace / only_official (mutually exclusive — same toggle as the in-app library lens). Page with limit + offset.

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• employer.search_candidates_for_job

  workorai

  Semantically rank discoverable (interviewed) candidates against one of the employer's own jobs, with a per-candidate fit score AND a white-box explanation. WORKFLOW for finding the best hire: 1) call with tier:'best' to get the strongest candidates (cover the required skills + proven in interview), cascade to tier:'good' then tier:'weak' only if you need more (read tierCounts to decide; paginate within a band via page.hasMore, not page.total); 2) each row carries matchExplanation — the white-box 'why' (the fit score, the skills the candidate PROVED in their interview, what they're missing, and a plain-English rationale) — use it to explain your shortlist on OUR data, not a black box; 3) for the few you shortlist, call employer.get_candidate_evidence(jobId, userId) for the interview facts + Q&A to write a deeper comparative review. Omit tier for the full ranked pool (back-compat). Returns NOT_FOUND when the job is missing / owned by another employer (no existence leak), or NOT_INDEXED / NO_CATEGORIES when the job is not indexed for semantic search yet (re-save / republish, then retry).

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• resource_use_instructions

  SuperSkill Registry

  Return the best safe next action for a mixed resource. Pass version to bind an immutable hosted release. Hosted skills expose explicit-consent exact native client install commands; upstream-only resources stay open-only.

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• customer_tiering_get_prep_code

  Customer Intelligence & Segmentation

  STEP 1 of 3 for the cheap sandbox path. Returns stdlib-only Python as `prep_code` (compact) and `prep_code_display` (readable, same logic), plus `reduction_spec` in words. Next: run one of those scripts (or your own from the spec) on the local CSV in your sandbox, then call customer_tiering_score_stats with the printed JSON. If the host needs code review first, show prep_code_display and wait for the user to say run/continue — then continue; do not invent a pause on hosts that allow silent runs. Python → MCP across turns is valid (ChatGPT Instant multi-step regressions are a host issue; Thinking/Auto or the next user turn still works). Do not invent rankings. If any step fails, fall back to customer_tiering with raw rows. This remote MCP NEVER reads the file — do NOT pass uploaded/attached file objects or platform upload handles. Call with no path args (preferred), or sandbox_path_hint as a plain string like 'book.csv'. Prefer this over customer_tiering when you have >~200 rows and a sandbox.

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