Skip to main content
Glama
205,112 tools. Last updated 2026-06-15 03:48

"Exploring the Concept of Thinking Carefully" matching MCP tools:

  • Return a canonical definition for a primitive Eurorack / synthesis concept and its relations to other concepts in the corpus. Use this for VOCABULARY questions, not module questions — when the user is asking what a term means or how two terms relate, not which modules implement it. Typical shapes: - "Is four-quadrant mult the same as through-zero AM?" → lookup_concept("four-quadrant mult") - "What's the difference between a gate and a trigger?" → lookup_concept("gate") - "Modular signal level vs line level — when does it matter?" → lookup_concept("modular signal level") - "Are clock dividers just pulse counters?" → lookup_concept("clock divider") - "Are polyphonic patch cables TRRRRRS?" → lookup_concept("polyphonic cable") Lookup is case-insensitive across three axes, tried in order: the canonical id ("through-zero-fm"), the canonical label ("Through-Zero FM (TZFM)"), and any registered alias ("tzfm", "through zero fm"). Spaces and hyphens are matched literally; the lookup does NOT normalize whitespace beyond lowercasing. If the term doesn't match anything, the response includes up to 5 substring-matched suggestions. Args: - name (string, required, min length 2): the term to look up. Examples: "AM", "ring mod", "four-quadrant mult", "TZFM", "clock divider", "gate", "trigger". Returns: { "concept": { "id": "amplitude-modulation", "label": "Amplitude Modulation (AM)", "description": "A multiplication of two signals: the carrier...", "aliases": ["am", "amplitude modulation", "amplitude mod"], "related_concepts": [ { "related_concept_id": "ring-modulation", "related_concept_label": "Ring Modulation (RM)", "relation_kind": "commonly_confused_with", "note": "AM with a unipolar modulator preserves the carrier..." }, ... ], "source_id": null, "citation_url": "https://learningmodular.com/glossary/...", "citation_quote": "Amplitude modulation is when..." } | null, "_meta": { "query": "<the name argument verbatim>", "matched_via": "id" | "label" | "alias" | "none", "concept_suggestions": [ { "id": "...", "label": "...", "matched_via": "alias", "matched_text": "..." } ], "feedback_hint": "...?" } } Relation kinds: - "related_to" — see-also link (default; symmetric in spirit). - "subtype_of" — X is a specific case of Y (RM ⊂ AM, TZFM ⊂ linear FM). - "inverse_of" — X is the opposite of Y (clock-divider ↔ clock-multiplier). - "commonly_confused_with" — they're distinct, but people conflate them (gate vs trigger, AM vs RM, modular level vs line level). When to cite: every concept carries either source_id or citation_url + citation_quote. Surface the citation when the answer affects a decision (e.g. "the corpus cites learningmodular.com — TRS cables are physically the same connector whether carrying balanced mono or unbalanced stereo; only the destination determines the role"). When the result is null and concept_suggestions are provided, present 2–3 closest matches to the user. If none look right, the corpus genuinely doesn't carry that concept — call report_gap with kind="missing_field" and tool_name="lookup_concept" naming the term and its expected definition.
    Connector
  • Create or overwrite an OpenAkashic markdown note. kind='claim' notes enter the contribution flow as private drafts with publication_status=requested. Sagwan then runs the first-pass guardrail: requested -> guardrail_passed or guardrail_rejected. A passed claim can later be approved/published by the publication workflow; rejected claims stay private with reviewer notes in frontmatter. Prefer claim for atomic reusable findings; Sagwan can later turn multiple related claims into a capsule. kind='capsule' notes stay private until you request publication review. Other kinds (playbook, concept, etc.) remain Closed-only working memory. Writable roots: personal_vault/, doc/, assets/ only. Formerly known as `check_contribution_status`: use claim_contribution_status to check submitted claim state. If you see tool-not-found errors for the old name, use claim_contribution_status instead. IMPORTANT: The response includes `path` — save this value and pass it to request_note_publication when you want to submit a capsule/synthesis for public review.
    Connector
  • USE THIS TOOL WHEN searching UK Acts and Statutory Instruments by title, phrase, or full-text. Returns ranked results: title, type, year, number, legislation.gov.uk URL, and next_steps hints (toc URI, section template). AFTER calling, chain to legislation_get_toc then legislation_get_section for structural drill-in. Filter discipline: `type` and `year` are exact-match. Use only when you already know the value. For currency-driven searches ("the recent Renters' Rights Act"), query by phrase alone and read the year from the results — guessing a year and filtering by it zeroes results when wrong. For broader concept queries across content, set `fulltext=True`. Authoritative source for UK primary and secondary legislation (legislation.gov.uk).
    Connector
  • Use this tool when the user asks BOTH what a financial figure is AND which filing reported it — for example "What was Apple's most recently reported revenue, and which 10-Q filed it?" or "Show me the accession ID for Tesla's latest net income" or "Which filing form reported Amazon's Q3 operating cash flow?" This tool returns a single fact plus its complete filing provenance: entity, concept, period, value, accession ID, filing URL, and form type (10-K, 10-Q, etc.). Use this INSTEAD OF `search_companies` when the user already names a company and wants a financial figure with its source filing — `search_companies` only resolves company identifiers and returns no financial data. Use this INSTEAD OF `get_company_fundamentals` when the user explicitly wants to know which filing or form type reported a number, or needs the accession ID — `get_company_fundamentals` returns metrics across multiple periods but omits filing provenance. Two lookup modes: (1) by fact_id (SHA-256 hash of entity_id|accession_id|concept|period_end|unit) for deterministic identity; or (2) by concept name (e.g., TotalRevenue, NetIncome, EPSDiluted, TotalAssets, OperatingCashFlow) plus a ticker to retrieve the most recently reported fact. Optionally pin a point-in-time cutoff via as_of_date (YYYY-MM-DD) — returns the latest filing accepted by SEC on or before that date, eliminating look-ahead bias. Check `_meta.pit_safe` in the response to confirm PIT correctness. DURATION: income-statement flow concepts (NetIncome, TotalRevenue, etc.) are reported over a window, and a single 10-K tags BOTH a 12-month figure and a 3-month Q4 stub at the same fiscal-year-end period_end. On a tie this tool returns the longer (headline) window, and every result carries `period_type` (instant | quarterly | half_year | nine_month | annual | duration) and `period_span_days` so you always know whether a number is a quarter or a full year — never present a 3-month stub as the annual figure. Provide either fact_id or concept (required). Returns empty result with error_code FACT_NOT_FOUND if no matching fact exists for the given concept and ticker. Available on all plans.
    Connector
  • Hybrid search — combines keyword + semantic search via RRF. Uses Reciprocal Rank Fusion (RRF) to merge exact-word results with meaning-based results. **This is the recommended tool for "discourses about X" / concept queries**, because the semantic side catches suttas that discuss a concept using different vocabulary (e.g. some mindfulness-of-breathing suttas use `assasati/passasati/dīghaṁ` instead of `ānāpānassati`). 💡 **Hints for the AI client:** - English queries usually work best (e.g. `mindfulness of breathing`) because the embedding model is multilingual but EN-primary. - Thai stop-word handling is weak. If a Thai query underperforms, the AI client should translate to Pāli/English first (see server instructions). - The default `limit=5` is often too small for a topic survey — use `limit=15-20` (max 20) for good coverage. - Ranking is by similarity, NOT canonical importance — locus classicus suttas (e.g. MN118, DN22) may rank below smaller suttas that happen to use the exact vocabulary. Treat results as a starting point, then call `get_sutta` for the canonical references.
    Connector
  • Submit a resolution verdict on a Ring 2 escalated dispute. Who can call this: 1. The publishing agent (always, for their own task disputes) 2. Eligible human arbiters (reputation_score >= 80 AND tasks_completed >= 10 in the same category) Verdict options: - 'release': worker wins -> triggers Facilitator /settle - 'refund': agent wins -> triggers Facilitator /refund - 'split': partial release + partial refund (requires split_pct = agent's refund %, 0-100) Side effects: - Updates the dispute row (status, winner, resolution_type='manual', agent_refund_usdc, executor_payout_usdc) - Triggers the appropriate payment flow via existing Facilitator paths - Emits dispute.resolved event on the event bus - Destructive: moves funds on-chain (use carefully) Args: params (ResolveDisputeInput): - dispute_id (str): UUID of the dispute - verdict (str): 'release' | 'refund' | 'split' - reason (str): justification (5-2000 chars, stored in audit trail) - split_pct (float, optional): required for 'split' verdict (0-100) - response_format (ResponseFormat): markdown | json Returns: str: Success message with dispute ID, verdict, amounts, and triggered payment action, or error message.
    Connector

Matching MCP Servers

  • A
    license
    -
    quality
    F
    maintenance
    Enables LLMs to perform conceptual search over local PDF/EPUB documents using a RAG pipeline with corpus-driven concept extraction and WordNet enrichment.
    Last updated
    3
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r
    Last updated
    1
    33
    24
    MIT

Matching MCP Connectors

  • Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…

  • Guardian Open Platform: content search, articles, sections, tags. Free dev key.

  • Fetch time-series data for 1–50 BLS series by SeriesID in a single API request (one query against the 500/day limit). Supports optional year range (up to 20 years per request) and BLS-computed period-over-period calculations (net change and percent change; a survey returns whichever it supports — CPI and PPI return percent change only, the inflation rate — so check bls_list_surveys first). When the total observation count would exceed the inline context budget, results spill to a canvas dataframe and the response includes a dataset.name handle for follow-up SQL via bls_dataframe_query. Use bls_search_series first if you need to resolve a concept to a SeriesID.
    Connector
  • [BROWSE] List active RRG listings, paginated, optionally scoped by brand_slug. Use when exploring the catalogue without a specific item in mind. If you already have a product name, SKU, brand, or descriptive keyword, call search_products FIRST, it is far cheaper than paging the whole catalogue (thousands of items). Returns a page of {limit, offset, total_count, has_more, next_offset, listings}; pass next_offset back to page through. Each listing has title, price in USDC, edition size, and remaining supply. Live on-chain minted count is in get_drop_details, not here. Next step after narrowing down: get_drop_details + initiate_agent_purchase.
    Connector
  • USE THIS TOOL WHEN searching UK Acts and Statutory Instruments by title, phrase, or full-text. Returns ranked results: title, type, year, number, legislation.gov.uk URL, and next_steps hints (toc URI, section template). AFTER calling, chain to legislation_get_toc then legislation_get_section for structural drill-in. Filter discipline: `type` and `year` are exact-match. Use only when you already know the value. For currency-driven searches ("the recent Renters' Rights Act"), query by phrase alone and read the year from the results — guessing a year and filtering by it zeroes results when wrong. For broader concept queries across content, set `fulltext=True`. Authoritative source for UK primary and secondary legislation (legislation.gov.uk).
    Connector
  • Get comprehensive RDF data for a DanNet synset (lexical concept). UNDERSTANDING THE DATA MODEL: Synsets are ontolex:LexicalConcept instances representing word meanings. They connect to words via ontolex:isEvokedBy and have rich semantic relations. KEY RELATIONSHIPS (by importance): 1. TAXONOMIC (most fundamental): - wn:hypernym → broader concept (e.g., "hund" → "pattedyr") - wn:hyponym → narrower concepts (e.g., "hund" → "puddel", "schæfer") - dns:orthogonalHypernym → cross-cutting categories [Danish: ortogonalt hyperonym] 2. LEXICAL CONNECTIONS: - ontolex:isEvokedBy → words expressing this concept [Danish: fremkaldes af] - ontolex:lexicalizedSense → sense instances [Danish: leksikaliseret betydning] - wn:similar → related but distinct concepts 3. PART-WHOLE RELATIONS: - wn:mero_part/wn:holo_part → component relationships [English: meronym/holonym part] - wn:mero_substance/wn:holo_substance → material composition - wn:mero_member/wn:holo_member → membership relations 4. SEMANTIC PROPERTIES: - dns:ontologicalType → semantic classification with @set array of dnc: types Common types: dnc:Animal, dnc:Human, dnc:Object, dnc:Physical, dnc:Dynamic (events/actions), dnc:Static (states) - dns:sentiment → emotional polarity with marl:hasPolarity and marl:polarityValue - wn:lexfile → semantic domain (e.g., "noun.food", "verb.motion") - skos:definition → synset definition (may be truncated for length) 5. CROSS-LINGUISTIC: - wn:ili → Interlingual Index for cross-language mapping - wn:eq_synonym → Open English WordNet equivalent DDO CONNECTION FOR FULLER DEFINITIONS: DanNet synset definitions (skos:definition) may be truncated (ending with "…"). For complete definitions, use the fetch_ddo_definition() tool which automatically retrieves full DDO text, or manually examine sense source URLs via get_sense_info(). NAVIGATION TIPS: - Follow wn:hypernym chains to find semantic categories - Check dns:inherited for properties from parent synsets - Use parse_resource_id() on URI references to get clean IDs - For fuller definitions, examine individual sense source URLs via get_sense_info() Args: synset_id: Synset identifier (e.g., "synset-1876" or just "1876") Returns: Dict containing JSON-LD format with: - @context → namespace mappings - @id → entity identifier (e.g., "dn:synset-1876") - @type → "ontolex:LexicalConcept" - All RDF properties with namespace prefixes (e.g., wn:hypernym) - dns:ontologicalType → {"@set": ["dnc:Animal", ...]} (if applicable) - dns:sentiment → {"marl:hasPolarity": "marl:Positive", "marl:polarityValue": "3"} (if applicable) - synset_id → clean identifier for convenience Example: info = get_synset_info("synset-52") # cake synset # Check info['wn:hypernym'] for parent concepts # Check info['dns:ontologicalType']['@set'] for semantic types # Check info['dns:sentiment']['marl:hasPolarity'] for sentiment
    Connector
  • Search the 96-indicator registry by keyword. Returns ranked matches (up to `limit`, default 10, max 50) with slug, branded name, underlying name, category, and canonical URL. Scoring is substring+prefix over slug, branded_name, name, and category — e.g. query 'savings' returns both The Buffer (personal saving rate) and The Safety Net (emergency savings survey). Use this when you want to discover which slug corresponds to a concept before calling `get_indicator`.
    Connector
  • [BROWSE] List active RRG listings, paginated, optionally scoped by brand_slug. Use when exploring the catalogue without a specific item in mind. If you already have a product name, SKU, brand, or descriptive keyword, call search_products FIRST, it is far cheaper than paging the whole catalogue (thousands of items). Returns a page of {limit, offset, total_count, has_more, next_offset, listings}; pass next_offset back to page through. Each listing has title, price in USDC, edition size, and remaining supply. Live on-chain minted count is in get_drop_details, not here. Next step after narrowing down: get_drop_details + initiate_agent_purchase.
    Connector
  • Search the BLS series catalog by natural language query, survey code, geographic area, or keywords to resolve cryptic SeriesIDs. Returns matching series with decoded components (survey, area, item, seasonal flag) and plain-language names. Use this before bls_get_series when you have a concept but not a SeriesID. Operates offline — no API quota consumed. Survey filter accepts two-letter codes (CU, CE, LN, LA, PC, JT, OE, EC, PR). Area filter accepts state names, MSA names, or FIPS area codes.
    Connector
  • Authenticated — submit an agency engagement enquiry on behalf of the caller for a founder-led discovery call. Persists an AgencyHandoff row routed to the agency inbox; the user is contacted by the team for a scoped proposal. Engagement scopes: workflow sprint (rapid agentic workflow implementation), proof-of-concept (validate a specific agent design in a bounded timeframe), pilot support (co-design and validate a production-ready pilot), advisory (ongoing architectural guidance across a product team). WHEN TO CALL: the user has identified a paid hands-on expert engagement need beyond self-service learning, and explicitly asks to talk to the team or book a discovery call. ALWAYS confirm with the user before firing — this creates a sales-visible record. WHEN NOT TO CALL: for free training / partnerships discussion (use handoffs.partnership); for support / billing / access (use handoffs.operator); proactively or as a sales push. BEHAVIOR: write-only, single insert, side-effecting. Auth: Bearer <token> (Firebase ID token, any plan). UK/EU residency. Response confirms the ticket id + scope so the user can reference it.
    Connector
  • Like palette_concept but with archive filtering and relevance controls. Use allowed_archives to restrict results to specific cultural traditions e.g. ['Japan'] for Japanese only. Use min_relevance to filter weak concept matches. Fixes cross-archive drift when cultural specificity matters.
    Connector
  • Submit a resolution verdict on a Ring 2 escalated dispute. Who can call this: 1. The publishing agent (always, for their own task disputes) 2. Eligible human arbiters (reputation_score >= 80 AND tasks_completed >= 10 in the same category) Verdict options: - 'release': worker wins -> triggers Facilitator /settle - 'refund': agent wins -> triggers Facilitator /refund - 'split': partial release + partial refund (requires split_pct = agent's refund %, 0-100) Side effects: - Updates the dispute row (status, winner, resolution_type='manual', agent_refund_usdc, executor_payout_usdc) - Triggers the appropriate payment flow via existing Facilitator paths - Emits dispute.resolved event on the event bus - Destructive: moves funds on-chain (use carefully) Args: params (ResolveDisputeInput): - dispute_id (str): UUID of the dispute - verdict (str): 'release' | 'refund' | 'split' - reason (str): justification (5-2000 chars, stored in audit trail) - split_pct (float, optional): required for 'split' verdict (0-100) - response_format (ResponseFormat): markdown | json Returns: str: Success message with dispute ID, verdict, amounts, and triggered payment action, or error message.
    Connector
  • Fetch the complete federal contract award history for a specific vendor. Read-only. No side effects. Idempotent. vendor_name: Company or organisation name e.g. Booz Allen Hamilton. Required. Fuzzy match used. jurisdiction: One of US, EU, or UK. Optional. Default US. Returns total award value, top awarding agencies, contract types, and recent awards with amounts and dates. Use this when researching a specific company's government contracting history. Use govcon_search_contract_awards instead when exploring a topic area without a specific vendor. Verified source: USASpending.gov. 4-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="govcon_fetch_vendor_contract_history", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".
    Connector
  • Fetch SEC XBRL frames for one concept × one period across all reporting companies. Inline response returns the top N ranked companies; the full frames response (all reporters) is materialized as df_<id> when a canvas is available, queryable via secedgar_dataframe_query. Accepts friendly names like "revenue" or "assets" (discover via secedgar_search_concepts) or raw XBRL tags. One call hits one XBRL tag — when a friendly name maps to multiple same-meaning tags, the response's `unqueried_tags` lists the others; call again per tag and UNION/COALESCE in SQL with an analysis-specific priority (e.g. SalesRevenueGoodsNet is goods-only). The response's `related_tags` separately flags alternate-DEFINITION tags a meaningful share of filers use as their primary line (e.g. cash incl. restricted cash, equity incl. noncontrolling interest) — a whole-universe screen on the base tag silently omits those filers; query them separately, but do not blindly union (the semantics differ). Response includes `value_distribution` and `period_end_range` to flag XBRL scale-factor anomalies and fiscal-year mixing.
    Connector
  • Search RedM/RDR3 docs by behavior, concept, OR exact token. Use when you don't have a specific native hash/name (use `lookup_native`) and the term isn't a known asset name in a large data table (use `grep_docs`). Hybrid mode (default) handles 'how do I X' queries ('teleport player', 'spawn vehicle', 'inventory add item') AND tokens ('addItem', 'weapon_pistol_volcanic', 'CPED_CONFIG_FLAG_') — fused via RRF over vector + BM25. Returns ranked snippets (path, breadcrumb, heading, snippet, score). Call `get_document({path, heading})` for full chunk content. `mode=semantic` for pure vector; `mode=lexical` for pure BM25. Filter via `category=vorp|rsgcore|oxmysql|natives|discoveries|jo_libs|learnings` or `namespace`. Community findings merged by default; `category=learnings` returns only findings. If you are retrying after a previous call returned no useful results, populate `prior_attempt` so the server can surface alternative wordings and learn what's missing from the docs.
    Connector
  • Search RedM/RDR3 docs by behavior, concept, OR exact token. Use when you don't have a specific native hash/name (use `lookup_native`) and the term isn't a known asset name in a large data table (use `grep_docs`). Hybrid mode (default) handles 'how do I X' queries ('teleport player', 'spawn vehicle', 'inventory add item') AND tokens ('addItem', 'weapon_pistol_volcanic', 'CPED_CONFIG_FLAG_') — fused via RRF over vector + BM25. Returns ranked snippets (path, breadcrumb, heading, snippet, score). Call `get_document({path, heading})` for full chunk content. `mode=semantic` for pure vector; `mode=lexical` for pure BM25. Filter via `category=vorp|rsgcore|oxmysql|natives|discoveries|jo_libs|learnings` or `namespace`. Community findings merged by default; `category=learnings` returns only findings. If you are retrying after a previous call returned no useful results, populate `prior_attempt` so the server can surface alternative wordings and learn what's missing from the docs.
    Connector