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594,623 tools. Updated 2026-09-20 23:02

"Techniques for Writing Files More Efficiently" matching MCP tools:

  • Return canonical synthesis / patching techniques with role-keyed module realizations drawn from the corpus. Use this when the user asks "how do I do X?" with X being a recognisable technique (low-pass-gate plucks, pinged-filter percussion, parallel multiband processing, complex-oscillator FM, karplus-strong pluck, clocked-delay feedback, modal-resonator excitation, wavefolder harmonics, envelope-follower ducking, Maths-style function-generator omnibus). It's also the right tool when the user has a module and asks "what's this good for?" — pass filter.module_id to retrieve every technique that references the module via its role_realizations. Each technique declares role_definitions (the roles the technique uses, each with required and optional affordances) and role_realizations (concrete modules that fill each role, with the affordances they provide). The model substitutes modules from the user's rack into roles by affordance match — DO NOT treat the realization list as exhaustive or as a recipe. Args: - filter (optional): { capability?, module_id?, text? } - capability: kebab-case capability id (see search_modules _meta.taxonomy). Returns techniques whose required *or* optional capability list includes this id. - module_id: "<manufacturer>/<module-slug>". Returns techniques that have a role_realization referencing this module. - text: free-text phrase. Substring-matches against technique id/label/description AND a curated alias table (technique_aliases) — that's the right surface when a user types evocative prose like "stuttering delay", "plucked string", "source of uncertainty" that doesn't grep against any kebab-case id. Two-way alias match: long alias ("source of uncertainty") matches short query ("uncertainty"), and vice versa. - When multiple filters supplied, AND-intersects. - Omit filter entirely to list all techniques. Returns: { "techniques": [ { "id": "low-pass-gate-pluck", "label": "Low-Pass Gate Pluck", "description": "Send a short envelope...", "required_capabilities": ["lowpass-gate"], "optional_capabilities": ["envelope-generator", "function-generator"], "role_definitions": [ { "role_id": "lpg", "description": "The vactrol-based or vactrol-emulating element. Strictly required...", "required_affordances": ["lowpass-gate"], "optional_affordances": [] }, ... ], "role_realizations": [ { "role_id": "lpg", "module_id": "make-noise/optomix", "affordances_provided": ["lowpass-gate"], "notes": "Two-channel vactrol-based LPG..." }, ... ], "canonical_instance": { "rationale": "...", "lineage": [ { "position": 1, "label": "Buchla 292 (1970)", "module_id": null, "notes": "..." }, { "position": 2, "label": "Tiptop Audio Buchla 292t", "module_id": "tiptop-audio/buchla-292t" }, ... ] }, "counter_canonical_notes": [ { "claim_pushed_back_against": "Optomix is the canonical pairing with Plaits...", "evidence": "The corpus catalogs 19 LPG-capable modules..." } ], "coverage": [ { "role_id": "voice", "realizations_count": 3 }, { "role_id": "lpg", "realizations_count": 19 }, { "role_id": "env", "realizations_count": 6 }, { "role_id": "clock", "realizations_count": 2 } ] } ], "_meta": { "filter": {...}, "feedback_hint"?: string } } How to use role data: - role_realizations are CURATORIAL SAMPLES, not exhaustive lists. The coverage[].realizations_count tells you how many are documented; other modules may fill the same role. - To find modules in the user's rack that can fill a role, use find_role_realizations(technique_id, role_id, available_modules). - canonical_instance is opt-in and sparse. Most techniques don't have one; that absence is information. When present, it documents a documented historical lineage (e.g., Buchla 292 → 292t → MMG → Optomix for low-pass-gate-pluck) — NOT a prescription. - counter_canonical_notes push back on likely training-data priors. When the user invokes a canonical-sounding claim that has a counter_canonical_note, surface the pushback. Errors: - "Module not found: <id>" if filter.module_id is supplied and unknown. - Empty techniques[] with a feedback_hint when filters produce no matches — call report_gap if the user expected coverage.
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  • List files in a Revdoku bucket. Pass limit and offset for paginated results; omit them to return all files for compatibility. Pass query to search by name/path, or folder to list one folder's files. Incoming messages use _email/in/<receipt-time>--<id>/message.eml, message.json, and attachments/. Read the JSON for decoded content and attachment paths. Use query=_email/in/ and paginate to find them; folder=_email/in returns only immediate files, not nested message folders. This is an offset file listing, not a durable inbox cursor.
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  • Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.
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  • Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.
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  • Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.
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  • Fast design check over the UI files you just changed. Returns issues with severity, category and file:line, in about 10 seconds. Cheap: five quick checks cost one review credit, so a whole editing session spends a fraction of one review. Use this one CONSTANTLY: after writing or editing a component, before committing, whenever you want to know if what you just wrote is sound. You do not need to ask the user first. It returns no score and no ready-made patch: fix the issues yourself in the files you already have open. When the user wants a score to keep, a patch to apply, or a review to quote, use review_files instead.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    An MCP service for AI-assisted reasoning and editing on long-form fiction projects. It builds a structured index from scene files for targeted context retrieval.
    381 npm
    1
    AGPL 3.0
  • A
    license
    A
    quality
    B
    maintenance
    Provides local, deterministic scoring and detailed auditing of text for AI-writing patterns via two read-only tools, with no network calls or language models.
    4
    2
    9 npm
    3
    MIT

Matching MCP Connectors

  • Open agent discussion boards, private proposals and conversations. Participation is optional.

  • Writing Style Checker (WSC) is a prose linter with an AI-tells detector: alongside classic checks (weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs) it flags 190+ research-cited words, phrases, and structural patterns overrepresented in AI-generated text — each with an explanation and source.

  • Fast design check over the UI files you just changed. Returns issues with severity, category and file:line, in about 10 seconds. Cheap: five quick checks cost one review credit, so a whole editing session spends a fraction of one review. Use this one CONSTANTLY: after writing or editing a component, before committing, whenever you want to know if what you just wrote is sound. You do not need to ask the user first. It returns no score and no ready-made patch: fix the issues yourself in the files you already have open. When the user wants a score to keep, a patch to apply, or a review to quote, use review_files instead.
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  • REQUIRED whenever you present rooms. Whenever you are about to mention, recommend, or describe one or more specific rooms to the user, you MUST call this tool with those room UUIDs INSTEAD of writing the rooms in text. This is mandatory even when there is only ONE matching room — show it as a single hero card, never describe a lone room in prose. Call this BEFORE writing any prose about the rooms; the cards must appear first, then a brief summary. Pass room UUIDs (from get_hotel_rooms or search results) in ranked order, best first, 1 to 8 rooms. ALWAYS pass check_in and check_out when you know the user's dates: card prices are then for those exact dates. Without dates, cards show a typical from-price that can differ a lot from any specific dates. Each card shows photo, Roomza score, view, bed, and price. NEVER ask the user whether they want to see cards or images — just call this tool.
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  • List files in the workspace, newest first (files group). Filter with nameContains rather than paginating broadly. Use get_file for a download URL or parsed contents. hasMore: true means more items exist — prefer narrowing filters over paginating, and pass nextPageToken only when every item is needed.
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  • Verify a photo's authenticity from a RAW camera file and its JPEG export, when the user asks for proof or a check that the photo is a genuine camera capture (not for feedback on the photo itself). Provide the files as attachments (raw_file = the camera RAW such as .CR2/.CR3/.NEF/.ARW/.RAF/.ORF/.DNG, image_file = the exported .jpg/.png), inline as raw_base64 + image_base64 (small files), or — for large files without attachments — call create_verification_upload first and pass the returned raw_object_key + image_object_key. Returns a verification id at once; the analysis runs in the background and takes from about a minute to 10 minutes or more, so call get_verification with the id repeatedly until status is completed. Counts against the monthly quota (free tier: 5/month).
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  • Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.
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  • Check whether anything has been sent to a capture URL yet, and read it. The status field is pending or captured. Pending is the ordinary answer before the sender fires and is not a failure. Set wait_seconds from 1 to 25 to wait efficiently for the first request. The call returns early when the capture changes. Zero reads the current state immediately. Unknown and expired IDs fail. No API key, no account and no sign up: call it directly.
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  • Calculate asset turnover: net sales divided by average total assets — how efficiently a company generates revenue from its asset base. Formula: Asset Turnover = Net Sales / Average Total Assets. WHEN TO USE: Use to compare revenue productivity across companies or years; a falling ratio suggests assets are not generating sales efficiently. WHEN NOT TO USE: Do NOT compare asset turnover across industries — capital intensity differs fundamentally (software vs manufacturing). BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive; identical inputs always produce identical outputs. Division by zero or non-finite inputs returns an explicit error instead of a number. RETURNS: JSON object { asset_turnover: number (e.g. 0.85 = 0.85x per year), inputs }. PARAMETERS: net_sales (required): Net sales / revenue for the period, e.g. 900000. Must be >= 0. begin_total_assets (required): Total assets at the START of the period, e.g. 1000000. Must be >= 0. end_total_assets (required): Total assets at the END of the period, e.g. 1100000. Must be >= 0.
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  • Import ONE still PNG or WebP as an Object or Character using one separate import allowance (Studio unlimited), zero credits. Use get_subscription_allowances first and proceed only when features.import is true. Before uploading, tell the user: transparency required, one clear complete subject, clean edges, consistent project style and camera, no text/watermark, up to 10 MB and 4096px per side; recommend 256px or more except intentional pixel art. No videos, GIFs or animated files; upload does not remove backgrounds or fix quality. Set confirmed only after this notice and approval. For local files, prefer POST /api/v1/asset-imports multipart file/projectId/name/kind/requestId rather than passing large base64 through model context. Persist requestId for safe network retries.
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  • Run a source-free compiler smoke test through the real Axint pipeline. Use immediately after installing or connecting Axint so the current agent proves it did more than start the MCP server. Use: call immediately after install or first MCP connection; use validate or run for project checks. Inputs: format changes rendering only; the smoke test has no project inputs. Effects: read-only built-in compiler smoke test; writes no files and uses no network.
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  • Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.
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  • Get Lenny Zeltser's expert writing guidelines for security reports and assessments. Provides guidance on tone, structure, clarity, executive summaries, and avoiding common writing mistakes. Includes rating-sheet items (the four lens sheets: structure, look, words, tone) as concrete reference points for grounded feedback. Works for any security document. This server never requests your documents and instructs your AI to keep them local—guidelines flow to your AI for local analysis. Note: For incident response reports specifically, use the ir_* tools which provide deeper section-by-section review criteria.
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  • Analyze multiple geometry files in a single batch request. Submit up to 10 files, receive a single quote, pay once, and get structured metadata for all files. Supports mixed formats. Read-only analysis — does not modify, convert, or repair files. Payment is required via x402 (USDC on Base) or card via MPP (Stripe). If no payment is provided, the response includes the total price and per-file breakdown. Retry with the payment argument containing "transaction", "network", and "priceToken". Partial success: if some files fail processing, you still receive results for the files that succeeded. Privacy policy: https://caliper.fit/privacy
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  • Creates a PowerPoint presentation (.pptx) at `path` from an array of slides, each {title, bullets:[…]}. Requires confirm=true — called without it, returns a preview of the deck instead of writing the file. The path must be somewhere Local MCP can write; Desktop/Documents/Downloads may need a one-time Files-and-Folders grant (System Settings → Privacy & Security → Files and Folders). Returns {created, path, slides}.
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  • Get the full text content of one file by id (large files are truncated; use ask_docs for targeted passages). Binary files (images etc.) return a short-lived download link instead. Audited.
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  • Fetch simplified GeoJSON for a boundary by its ONS census code. Safe to embed directly in generated HTML map files. At the default tolerance (0.0001°) a constituency polygon shrinks from ~4,000 vertices to ~200–400 with no visible difference at normal map zoom levels. Prefer this over get_boundary_geojson_by_code() when writing Leaflet map pages — the full geometry is large enough to exhaust your context window before you can finish writing the HTML.
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