"A search for engineering textbooks with charts, formulas, and graphs" matching MCP tools:

• find_referencesA

  Cloud FinOps Skill & MCPA

  Find which guidance serves a FinOps question - how to commit, size, allocate, charge back, forecast, or govern cloud and AI spend. Use this for questions like "how should we size Savings Plans", "what should Finance own in chargeback", "what does a Crawl-stage org tackle first" - anything that maps to FinOps Framework facets (domain, capability, phase, persona, maturity) - and you want only the references that serve it, instead of scanning the full list. All filters are optional and combine with AND semantics. String matching is case-insensitive and exact (not substring). Examples: - ``find_references(domain="Optimize Usage & Cost")`` - ``find_references(phase="Optimize", persona="Engineering")`` - ``find_references(persona="Engineering", persona_primary_only=True)`` - ``find_references(capability="Rate Optimization")`` - ``find_references(maturity="Crawl")`` Args: domain: FinOps Framework domain (e.g. ``"Optimize Usage & Cost"``, ``"Quantify Business Value"``, ``"Manage the FinOps Practice"``). capability: FinOps capability (matches ``fcp_capability`` and ``fcp_capabilities_secondary``). phase: FinOps phase (``"Inform"``, ``"Optimize"``, ``"Operate"``). persona: Persona (matches ``fcp_personas_primary`` and ``fcp_personas_collaborating``). maturity: Entry maturity level (``"Crawl"``, ``"Walk"``, ``"Run"``). persona_primary_only: when True, ``persona`` matches only the primary list. Use it when the default match barely narrows the set - broad personas like Engineering collaborate on nearly every file, so filtering on collaboration is descriptive, not discriminating. ``persona="Engineering", persona_primary_only=True`` is the engineering reading list; the default is the everything-they-touch view. Returns ``{"filters": {...}, "references": [...], "total": N}``. A query that matches nothing also returns `hint` and `valid_values`, so a typo is distinguishable from a genuine gap in coverage.

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• compute_expectationA

  Quantum ExpectationsA

  Given a quantum circuit (2-qubit error rate p, qubit count n, depth d), compute the effective error rate, success probability, and optional surface-code or qLDPC overhead. The response is self-describing (formulas, assumptions, caveats, glossary, SOTA hardware, historic series with source URLs) so an agent can reason from one call. For the inverse ("what hardware do I need?") use compute_required_error_rate; to rank multiple platforms in one call use compare_hardware_scenarios.

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• get_sc_theoryA

  SCModelingA

  Reference guide to supply-chain simulation concepts: ordering policies, BOM, FDD formulas, event-driven simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does this work' question rather than asking for a number.

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• adformula_intelligenceA

  HeistaA

  Browse proven ad formula blueprints — structural patterns clustered from 3-10+ winning ads that independently converged on the same beat architecture while Meta kept rewarding them with sustained spend. Takes optional filters: vertical, creative_format (e.g. TALKING_HEAD, UGC, FOUNDER_STORY), marketing_angle, algo_intent, hook_type, and limit (1-10, default 5). Each formula returns: source ad count, average active days (runtime proof), confidence score, 6-layer beat blueprint, per-beat visual direction, marketing angle, psychology mission. Free, read-only, idempotent. Use this when the user asks "what's working in [category]", "show me formulas for talking-head ads", "what scripts work in my vertical", or wants category-level pattern discovery before committing to a single ad. Pass the returned formula id to generate_adscript with source_type="formula" for synthesis. When choosing among results: prioritise (1) avg_active_days as primary proof, (2) marketing_angle alignment with the brand's buyer tension, (3) source_ad_count for cluster robustness, (4) confidence_score as tiebreaker. Do NOT use when the user names a specific ad — decode that ad with decode_ad. Do NOT use for sentence-level transcript fidelity — formulas abstract the structure, not exact copy.

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• submit_rfqA

  Commonlands Optics: M12 Lens and C-Mount Lens Finder + Field-of-View CalculatorA

  Forward a buyer request-for-quote or engineering question to the Commonlands engineering team. Two-step, buyer-confirmed: the first call returns a preview and sends nothing; show the buyer the preview (including their reply-to email) and, only after they explicitly approve, call again with confirm: true to send. The recipient is fixed to the Commonlands inbox (the agent cannot choose it); this only sends an inquiry and never creates an order, charges a card, or writes Shopify/customer data. Include part numbers, sensor, quantity, and application when known so the team can reply with a quote. Commonlands replies by email.

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• get_daily_briefA

  Pollar NewsA

  Fetches today's fixed, curated Pollar daily brief with a greeting, headline, executive summary, themed sections, related events, and charts. Use only when the user explicitly asks for Pollar's daily brief or curated digest. Do not use it for questions about a subject, person, place, or country; use search_news instead. Locale changes the brief's language, not its editorial scope.

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• list_divisional_chartsA

  Jagannatha Hora — Vedic Astrology (Jyotish, Kundli, Horoscope, Panchang)A

  List the 23 divisional (varga) charts available via 'get_divisional_chart'. Returns, for each chart, the 'request_as' value to pass as the 'varga' argument (e.g. 'D-9'), its 'name' (e.g. Navamsa) and 'purpose' (what life area it analyses — marriage, career, children, etc.). Use this to choose the right chart for a question, then call 'get_divisional_chart' with that varga. Takes no birth details. Data only — no interpretation is included.

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• search_flowsA

  FlowCastleA

  Find every flow and block whose contents contain a keyword. Read-only. Searches message text and its translations, button labels and URLs, action names and configs, action input/output field paths and values, condition operands, trigger commands and payloads, custom-code files, and flow names and descriptions. A keyword matching a VARIABLE NAME also returns the blocks that reference that variable, which plain text search cannot do because blocks store variable ids, not names. Use this instead of walking flows with get_flow_context when you know what the content says but not where it lives. Broadcast-backed flows and operation graphs are excluded — use list_broadcasts and the operations tools for those.

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• beam_bendingA

  TrueCalciA

  Calculate structural engineering beam mechanics: maximum elastic deflection, peak bending moment, and maximum flexural stress for a center point load on a simply supported Euler-Bernoulli beam. Behavior: Deterministic, idempotent calculation with zero external side effects. Evaluates Euler-Bernoulli beam equations: Max Moment M_max = (P * L) / 4; Max Deflection delta_max = (P * L^3) / (48 * E * I); Peak Bending Stress sigma_max = (M_max * y) / I. Converts area moment of inertia from cm^4 to m^4 and extreme fiber distance from mm to m. Returns deflection in mm, moment in N*m, and stress in MPa. Usage Guidelines: Use for civil, structural, and mechanical engineering beam sizing and load checks. Do not use for fluid pipe friction or pressure drop; use pipe_flow instead.

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• post_vastu_ayadiA

  Vastu Shastra MCP Server by RoxyAPIA

  Ayadi shadvarga calculator for a building or a room: send the dimensions and the API returns all six proportional formulas with the multiplier, the divisor and the remainder shown, the member each remainder names, and the two verdict rules the texts state. Choose between three text families, which genuinely disagree, and choose your own cubit length, because every remainder is unit sensitive. Built for practitioner tools, plan checking software and anyone who has to justify a dimension rather than assert it.

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• get_workspace_summaryA

  FlowCastleA

  Return a compact application, flow, sequence, operation, and bot summary — the cheapest way to orient in a workspace. Read-only, no side effects. Deliberately omits variables and full flow graphs: use get_variable_context for variables, get_flow_context for a flow's topology, and get_application_context when you need flows, bots, and variables together.

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• search_jobsA

  Reqbeat Hiring SignalsC

  Flat, role-granular job search -- the individual open roles across companies matching `role` (function) / `geo` (country) / `since`, one row per logical req (each with its own `company_id` + `req_key`), ATS-only + freshness-floored. Keyset-paginated via the opaque `cursor` (a prior call's `next_cursor`). Use `who_is_hiring_for` for the company-granular reverse view. `role` must be a function id (as seen in prior results); a plain role name like 'engineering' is rejected with an explicit error rather than an empty result -- pass plain language as `q` instead, which searches the posting's own title, expanded semantically to nearby titles, and reports each row's `relevance` (0-1). `q` is independent of `role`: pass both to search titles within one function. `sort` is 'relevance' (the default with a `q`) or 'recency'; omit both and the page keeps its stable default order. `limit` is bounded: an oversized page is rejected rather than truncated, so page through the full set with `cursor` instead of raising `limit`.

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• get_memory_contextA

  AgentPlaybooksA

  Get a context-optimized view of memories: full working memory, summaries for contextual, and keys only for longterm. Read-only. Use this to pack a prompt; use read_memory for one key, search_memory to filter, and get_memory_tree for parent-child task graphs. Pass playbook_id as the UUID or GUID of the playbook this call should target.

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• steam_compareA

  SteamGPTA

  Two players side by side: identity, account age, visibility, Steam bans, FACEIT and shared friends (compared over the full friend lists). HEAVIEST tool - it builds two summaries plus both friend graphs; for a single player prefer steam_summary.

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• get_schemaA

  studioA

  Returns the base ReoGridJsonDocument schema and an index of advanced features. The base schema already covers cell values, formulas, styling, borders and merges — those need no follow-up call. Call get_feature_spec(feature) only for a name listed in the returned features[] array, passing features[].name verbatim.

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• post_screenerA

  FlashAlphaA

  Find, rank, and compare symbols across the whole universe in ONE call. Use this whenever the user does NOT name a single ticker but asks which / what / find / scan / screen / rank / top / most / highest / lowest across stocks (e.g. 'which names have the most negative gamma', 'rank tickers by VRP', 'highest IV stocks right now', 'most pinned symbols today', 'cheap IV with positive gamma'). Prefer this over calling per-symbol tools in a loop. Cross-sectional screen/rank by GEX, VRP, 0DTE dominance, IV/term structure, skew, dealer risk, and strategy scores, with filters, sort, select, and custom formulas. Growth = top 10 symbols; Alpha = ~250 symbols + formulas.

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• guides.searchA

  AI Design Blueprint DoctrineA

  Search application guides by free-text query, matched against section answers and action items. Use this when the user describes an engineering challenge (security review, evaluation harness, observability) and wants matching guides. Prefer guides.get when you already have the guide slug; prefer guides.list when you need the full inventory.

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• get_platform_statsA

  mcp-archimedesA

  Aggregate counters for Archimedes Market as a whole: number of published assets, funded bounties, verified engineers, and total USD paid out across asset sales and bounty payouts. Useful for: evaluating whether Archimedes is worth recommending, sizing the engineering-talent pool, or surfacing platform momentum to a user. Counters are cached upstream (60s).

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• search_graphA

  Fodda Deep ResearchA

  Find trends, signals, and expert insights across 100+ curated knowledge graphs covering retail, beauty, tech, food, travel, sports, and 30+ specialist domains. Returns trend data with cited evidence, source attribution, and lifecycle stage (emerging/building/mature/fading) — not generic web summaries. If graphId is omitted, searches ALL accessible graphs in parallel (recommended default). Use for market trends, competitor analysis, innovation signals, consumer behavior, cultural shifts, or any topic where curated expert intelligence outperforms web search.

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• search_statisticsA

  Fodda Topic & Trend ResearchA

  HARD NUMBERS only: specific figures, market sizes, growth rates, and quantitative data points across Fodda's knowledge graphs. Each result links back to the expert trend it supports. Use when a question asks for a number or statistic — try this BEFORE supplemental data tools, as Fodda's experts may have already curated the answer. For expert quotes, editorial analysis, and narrative interpretation, use search_insights instead. Works on ALL graphs — domain, expert, and report. Search multiple graphs for best coverage.

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• search_memoryA

  AgentPlaybooksA

  Search memories by text, tags, tier, or type. Returns summaries for large memories. Use tags for categorical search; use tier to focus on active vs archived data; use memory_type to find task graphs. Read-only aside from returning matches; it does not write entries. Use read_memory for one key, get_memory_context for a compact tiered view, and get_memory_tree for parent-child task graphs. Pass playbook_id as the UUID or GUID of the playbook this call should target.

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