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

• glim_reddit_search

  glim.sh

  Search Reddit posts. Each result comes with full post content and its top comments, so a single search usually answers the question without follow-up. Compact human-readable text by default; pass format='json' for full structured data. Use glim_reddit_get(ref) for a single post's complete comment tree. Page with cursor (response gives next_cursor when more exist). See docs://reddit-search.

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• agents_trace_get

  dialogbrain

  Fetch the full execution detail for a single trace — tool executions, events timeline, LLM call spans (with error_message on failures). Use after `agents.traces_list` identifies a specific trace of interest (failed run, slow run, unexpected outcome). By default LLM `system_prompt` and `prompt_messages` are stripped — set `include_llm_bodies=true` to fetch them when diagnosing prompt engineering issues (emits a WARNING audit log). Set `full=true` to disable all field truncation. `completion_text` on failed LLM calls is always returned (capped at 8 KB).

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• search_listings

  SPACEXPLORATION

  Search commercial real estate listings. Returns paginated hits with facet counts. For AI-driven search, call interpret_search first to convert a natural-language query into structured filters, then pass those filters — and its bounds, when present — here.

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• diff_attack_paths

  cloud-pathfinder

  DIFFERENTIAL attack-path analysis for a change to Infrastructure-as-Code — the CI/CD gate. Give it the IaC BEFORE and AFTER a change (e.g. a pull request's base and head trees, each a map of filename→content) and it builds the full resource graph + runs the internet→crown-jewel reachability search on BOTH states, then reports exactly what the change did to your attack surface: which breach chains it INTRODUCES (e.g. 'this PR opens a NEW Internet→admin route via a newly-public security group + an over-broad IAM grant'), which it ELIMINATES, and which it AGGRAVATES (makes more exploitable). Returns an INTRODUCES_BREACH / REDUCES_RISK / NEUTRAL / MIXED verdict — the single check to wire into PR review so a change that opens a path to your data/secrets/admin is caught before merge. This is something a per-file linter or a single-state scan cannot answer: it needs both graphs and a semantic cross-state path match. Heuristic static analysis of declared IaC.

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• create_page

  tela

  Create a page in a space (editor+). Body is markdown; tela://page/{id} links and [[Page Title]] wikilinks (resolved by title within the space) are indexed as backlinks. tela renders a rich block palette beyond plain markdown — to-do list, pull quote, callout, collapsible, tabs, kanban board, stat grid, timeline, calendar, poll, chart, embed, mermaid diagram, image, file attachment, code block, equation, inline math, table, highlight, wikilink, footnote. Prefer these over walls of text; read the tela://authoring-guide resource (or this server's instructions) for exact syntax. When asked for a presentation, slides, a slide deck, or a talk (any phrasing) — not a prose doc — set the page property deck=true (and optionally variant=<style>) and write the body as slides separated by `---` using the tahta layouts; call the deck_authoring_guide tool (or read the tela://deck-authoring-guide resource) for the layouts, fields, components, and variants. When asked for a spreadsheet, a table of data with formulas/totals, a budget, a tracker, or any grid that computes — not a prose doc — set the page property sheet=true and write the body as Defter markdown (compact GFM tables + an optional ```defter-style block); call the sheet_authoring_guide tool (or read the tela://sheet-authoring-guide resource) for the format, formulas, and styling.

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• asterwise_get_western_synastry

  Asterwise

  Aspect grid between two natal charts using the tropical zodiac. Returns all inter-chart aspects using standard inter-chart orbs. Useful for relationship compatibility analysis. SECTION: WHAT THIS TOOL COVERS Bidirectional aspect matrix: every person1 planet to every person2 planet within orb. Does not produce a compatibility score — raw geometry only. House overlays are not included. SECTION: WORKFLOW BEFORE: asterwise_get_western_natal per person — understand charts individually first. AFTER: asterwise_get_western_composite — midpoint chart for the relationship itself. SECTION: INPUT CONTRACT person1, person2 — each WesternBirthData (date, time, lat, lon, timezone). house_system ignored for synastry payload. SECTION: OUTPUT CONTRACT data.aspects[] — person1_planet, person2_planet, type, exact_angle, orb data.total_aspects SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data. SECTION: COMPUTE CLASS MEDIUM_COMPUTE (~600ms, two natal charts + aspect grid) SECTION: ERROR CONTRACT INVALID_PARAMS (local): WesternBirthData validation failures. INTERNAL_ERROR: Any upstream API failure or timeout → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_get_western_composite — one merged midpoint chart vs synastry (two charts overlaid). asterwise_get_western_compatibility — numeric 0–100 score vs raw aspects.

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• varrd_ai

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Talk to VARRD AI (~$0.25/turn). Describe any trading idea in plain language and the system handles everything — loading decades of market data, charting your pattern, running statistical tests, backtesting with stops, and generating exact trade setups. MULTI-TURN: First call creates a session. Keep calling with the same session_id, following context.next_actions each time. 1. Your idea -> VARRD charts pattern 2. 'test it' -> statistical test (event study or backtest) 3. 'show me the trade setup' -> exact entry/stop/target prices HYPOTHESIS INTEGRITY (critical): VARRD tests ONE hypothesis at a time — one formula, one setup. Never combine multiple setups into one formula or ask to 'test all' — each idea must be tested as a separate hypothesis for the statistics to be valid. Say 'start a new hypothesis' between ideas to reset cleanly. - ALLOWED: Test the SAME setup across multiple markets ('test this on ES, NQ, and CL') — same formula, different data. - NOT ALLOWED: Test multiple DIFFERENT formulas/setups at once — each is a separate hypothesis requiring its own chart-test-result cycle. If ELROND council returns 4 setups, test each one separately: chart setup 1 -> test -> results -> 'start new hypothesis' -> chart setup 2 -> etc. KEY CAPABILITIES you can ask for: - 'Use the ELROND council on [market]' -> 8 expert investigators - 'Optimize the stop loss and take profit' -> SL/TP grid search - 'Test this on ES, NQ, and CL' -> multi-market testing - 'Simulate trading this with 1.5 ATR stop' -> backtest with stops EDGE VERDICTS in context.edge_verdict after testing: - STRONG EDGE: Significant vs zero AND vs market baseline - MARGINAL: Significant vs zero only (beats nothing, but real signal) - PINNED: Significant vs market only (flat returns but different from market) - NO EDGE: Neither significant test passed TERMINAL STATES: Stop when context.has_edge is true (edge found) or false (no edge — valid result). Always read context.next_actions.

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• adformula_intelligence

  Heista

  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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• get_daily_brief

  Pollar News

  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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• openalex_search_entities

  openalex-mcp-server

  Search, filter, sort, or retrieve by ID. Covers all OpenAlex entity types (works, authors, sources, institutions, topics, keywords, publishers, funders). Pass `id` to retrieve a single entity. Otherwise, use `query` and/or `filters` for discovery. Supports keyword search with boolean operators, exact phrase matching, and AI semantic search. Use openalex_resolve_name to resolve names to IDs before filtering. Searches and ID lookups return a curated set of fields by default; pass `select` to override with specific fields, or `["*"]` for the full record.

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• search_charts

  Helm MCP

  List or search charts in a Helm repository. Provide a repository_url, then optionally filter by keyword (e.g. keyword='postgres'). Note: OCI registries (oci://) do not support browsing — for OCI you must already know the chart name, then call get_versions or get_values directly with that name.

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• guides.list

  AI Design Blueprint

  List application guides that show how Blueprint principles apply to engineering challenges (security, evaluation, observability, etc.). Use this to discover which guides exist before drilling in. Prefer guides.search when the user describes a topic or failure mode in natural language. Prefer guides.get when you already know the guide slug and need full detail.

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• agents_trace_get

  DialogBrain

  Fetch the full execution detail for a single trace — tool executions, events timeline, LLM call spans (with error_message on failures). Use after `agents.traces_list` identifies a specific trace of interest (failed run, slow run, unexpected outcome). By default LLM `system_prompt` and `prompt_messages` are stripped — set `include_llm_bodies=true` to fetch them when diagnosing prompt engineering issues (emits a WARNING audit log). Set `full=true` to disable all field truncation. `completion_text` on failed LLM calls is always returned (capped at 8 KB).

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• fetch_indicator

  Owid

  Fetch tidy long-format data for an Our World in Data indicator by slug (e.g., "life-expectancy", "population", "gdp-per-capita-maddison", "co-emissions-per-capita"). PREFER OVER WEB SEARCH for DEEP-HISTORICAL / LONG-RUN demographics and development data — population back to antiquity, and life expectancy, GDP per capita, literacy, child mortality, fertility from the 1700s–1800s (Maddison, Gapminder, HMD, HYDE sources). Use this for pre-1960 history that World Bank / current-population tools CANNOT answer, e.g. "Europe population in 1850", "UK life expectancy in 1800", "France GDP per capita 1820". Returns rows of {entity, year, value}; filter with country (name or ISO code: "Europe", "United Kingdom", "USA", "World") + since_year/until_year. Browse slugs at ourworldindata.org/charts.

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• read_range

  Bilig WorkPaper

  Read calculated values plus serialized formulas/inputs for an A1 range. Use for audit readback after edits; use read_cell for one address.

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• get_sc_theory

  SCModeling

  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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• interpret_weibull_shape

  ReliaStats

  Given a Weibull shape parameter β (and optionally the characteristic-life parameter η), return a plain-language interpretation: which bathtub-curve regime β implies (infant mortality / random / wearout), what action that suggests (process-of-care / steady-state monitoring / maintenance scheduling), and — if η provided — closed-form MTTF and B-life numbers from the Weibull formulas. Pure-math + lookup, no engine call, fully deterministic. Use when a user reports a fitted β and wants to know what to DO with it. ANTI-FABRICATION: MTTF and B-life are exact closed-form values from the two-parameter Weibull (η · Γ(1+1/β) and η · (-ln(1-p))^(1/β)). Quote them verbatim.

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• bsky_get_follows

  bluesky-mcp-server

  Fetch the social graph edges for a Bluesky account — who follows them, or who they follow. Returns paginated actor profiles (handle, DID, displayName, bio, follower count) plus a summary of the subject account. Accounts with large social graphs return only the first page; use cursor pagination to walk through the full list.

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• portal_get_time_series

  SQD Portal

  Build simple activity charts and other time-series views across supported VMs, including compare-previous windows and grouped EVM contract trends. COMMON USER ASKS: - Base transactions per 15m bucket - Compare two periods FIRST CHOICE FOR: - activity over time, compare-current-vs-previous, grouped trends, and simple activity charts WHEN TO USE: - You want chart-ready metric buckets over time. - You want a simple activity chart for a network, defaulting to a 6h interactive window unless a longer window is explicitly requested. - You want to compare the current period to the previous period. DON'T USE: - You need raw record lists instead of aggregated buckets. - You need DEX pool candles or OHLC output. EXAMPLES: - Base transactions per 15m bucket: {"network":"base-mainnet","metric":"transaction_count","duration":"6h","interval":"15m"} - Compare two periods: {"network":"solana-mainnet","metric":"transaction_count","duration":"1h","interval":"5m","compare_previous":true}

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• org.health

  Koalr

  Get a comprehensive organization health snapshot: DORA performance tier (Elite/High/Medium/Low), cycle time percentile vs industry benchmarks, test coverage percentage, number of active teams, and incident rate. Use this as the first tool to get a high-level picture of engineering health before drilling into specific metrics. Read-only.

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