"Pine Script" matching MCP tools:

• list_docs

  Pine Script

  USE WHEN discovering what Pine Script v6 documentation is available. Returns a categorised list of doc file paths with one-line descriptions. AFTER calling this tool, call get_doc(path) for small files or list_sections(path) then get_section(path, header) for large files (ta.md, strategy.md, collections.md, drawing.md, general.md). Data sourced from bundled Pine Script v6 documentation.

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• get_doc

  Pine Script

  USE WHEN reading the full content of a Pine Script v6 documentation file. Returns the file content; when limit is set, a header shows the char range and offset to continue reading. AFTER calling this tool, use offset=<end> to continue if the header indicates more content is available. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md), prefer list_sections() + get_section() instead. Data sourced from bundled Pine Script v6 documentation.

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• list_sections

  Pine Script

  USE WHEN navigating a large documentation file before reading a specific section. Returns a newline-separated list of # and ## headers (### excluded) in the file. AFTER calling this tool, call get_section(path, header) with a header from this list. Data sourced from bundled Pine Script v6 documentation.

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• get_section

  Pine Script

  USE WHEN reading a specific named section from a Pine Script v6 documentation file. Returns the section content from the matched header to the next same-level header, with file path and line range. AFTER calling this tool, call list_sections(path) if the header was not found, or get_section() again with a child header for a narrower subsection. Data sourced from bundled Pine Script v6 documentation.

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• search_docs

  Pine Script

  USE WHEN finding documentation sections that match specific terms across all Pine Script v6 docs. Returns up to max_results sections ranked by match count, each with a preview and a get_section() call hint. AFTER calling this tool, call get_section(file, header) for each result you want to read in full. Data sourced from bundled Pine Script v6 documentation.

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• get_functions

  Pine Script

  USE WHEN browsing valid Pine Script v6 functions, optionally filtered to a namespace. Returns function names grouped by namespace (e.g. ta.*, strategy.*) or filtered to the requested namespace. AFTER calling this tool, call validate_function(fn_name) to check a specific name, or get_section() to read its documentation. Data sourced from bundled pine_v6_functions.json.

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• get_document

  RedM Mcp

  Fetch full markdown of a doc by `path` (as returned by `browse`, `semantic_search`, or `grep_docs`). Use to retrieve full content after a search snippet looks promising. Pass `heading` (full breadcrumb like `Character Management > Inventory Management`, or just the leaf — case-insensitive, fuzzy) to fetch only that section. Deep-heading matches auto-prepend the H2 parent's intro for context. For individual script natives prefer `lookup_native`. The largest rdr3_discoveries lua data tables are keyed catalogs: call with no `heading` to list their top-level keys, then pass a key as `heading` to fetch that one entry; use `grep_docs` to search values inside. For code symbols (`addItem`) use `grep_docs`. Community findings use `learning:N` paths, not `learnings/<slug>.md`. On 404 returns available headings + cross-file hints.

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• grep_docs

  RedM Mcp

  Find an EXACT literal token in raw doc files (markdown + lua). Use for specific weapon/ped/animation/prop/interior/zone names (`weapon_pistol_volcanic`, `a_c_bear_01`, `p_campfire01x`), known hashes (`0x020D13FF`), walkstyles/clipsets (`MP_Style_Casual`, `mech_loco_m@`), or any string you'd `grep` for. NOT for behavior/concept queries (use `semantic_search`) or script-native hash/name lookup (use `lookup_native`). REQUIRED for tokens inside the largest rdr3_discoveries data tables (audio_banks, ingameanims_list, cloth_drawable, cloth_hash_names, object_list, megadictanims, entity_extensions, imaps_with_coords, propsets_list, vehicle_bones) — only preview-indexed for embeddings, so `semantic_search` will NOT find tokens in them. Optional: `contextBefore`/`contextAfter` for ±N surrounding lines (saves a follow-up `get_document` call); `filesOnly: true` to get paths only (cheap exploration); `multiline: true` for cross-line patterns (`(?s)foo.*bar`). Pattern uses Rust regex syntax (rg engine). PREFER one targeted call over giant `a|b|c|d|e` alternations — split into separate calls; alternations rarely improve recall and bloat the regex automaton. Returns matched lines with path + line number. Long matched lines are windowed ±60 chars around the match (…); to read around a hit, use `read_lines({path, start})` for the preview-only mega-tables listed above (get_document holds only their ~80-line head), or `get_document({path})` for ordinary docs. If you are retrying after a previous pattern returned no matches, populate `prior_attempt` so the server can record what didn't work and steer alternative spellings.

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• query_json

  mcp

  Use this when you need to pull specific values out of a JSON document by JSONPath and getting the path exactly right on deeply nested or large structures matters. Evaluates a JSONPath subset — $ (root), .name or ['name'] (child), [n] (index, negative allowed), [*] (wildcard), .. (recursive descent), and [start:end] (slice) — and returns every matching value in document order. Prefer this over hand-walking nested JSON, where it is easy to miscount array indices or miss a deep match. Filter (?()) and script (()) expressions are not supported and are rejected with a message naming the supported subset. Deterministic: same input, same output. Example: path "$.store.book[-1].title" over {"store":{"book":[{"title":"A"},{"title":"B"}]}} -> matches ["B"], count 1.

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• analyze_audio

  Clueso

  Analyze an audio file. Modes: - transcript: Speech-to-text with word-level timestamps. Works on BOTH speech and sung lyrics — routes to a music-aware provider when content is detected as music. Use to get `words[{w,start_ms,end_ms}]` for caption timing, script editing, or word-level visual sync. Note: features.has_speech may report false on pure music while transcript still successfully extracts lyrics. - silences: list of silent regions with start/end/peak. Use for auto-trim, smart-split, or pause-aware editing. - beats: tempo (bpm) + beat positions for music tracks. Returns empty for non-music. Use to align animations/zooms to a beat. - features: duration, peak/rms/lufs loudness, speech-vs-music heuristic. Cheap dispatcher — call once to decide which other mode to use, or to get duration_ms for source_duration when calling add_audio. Source: provide exactly one of mcp_upload_id (from upload tool) or file_url (already-public URL, e.g. a find(type='music') result or Clueso CDN file). Optional time range: range_start_ms / range_end_ms crops the analysis window.

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• hatch

  Hatch

  Create a NEW site (a 'roost') and return its public URL in one call. Returns `{ tenantId, slug, url, apex, uploads? }` — show `url` to the user and remember `tenantId`. NEVER call hatch twice for the same site — use `convert` to rename or change tier, and `upload`/`deploy` for content updates. Pick `apex` from the user's intent (homes / estate / land / wedding / events / agency / site / omit for theroost.dev). Do NOT invent other apexes. Four ways to call it: • Omit `manifest`, `site`, and `script` → a placeholder page is published instantly (best zero-token first turn). • Pass `manifest` (file list with sizes) → returns presigned `uploads[]`; you PUT each file's bytes directly to its URL. PREFER this for any project with images, fonts, video, or more than a few KB of HTML. • Pass `site` (inline files map) → small text-only sites only. Files are sent in the request body, so this is expensive in tokens for anything bigger than a handful of HTML/CSS files. • Pass `script` → advanced: full server-side code as one ES module (1.5 MiB max, text only — NEVER base64-embed binaries here).

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• niche_draft_revise

  Niche — Editorial Intelligence

  Applies the values you pass to a specific output. Accepts any subset of the output's fields: caption, hashtags, or partial script updates (hook / body / cta / hook_tweet / body_tweets / title / subtitle / pull_quote / cover_slide / slides / cta_slide / alt_text / card_headline, where card_headline rewords the image card's header). Pass `apply_hook_variant_index` to splice an existing hook_variants[N] into the live hook in one move without rewriting the rest. If you pass no editable field (or values identical to the current draft) it changes nothing and returns `status:'no_change'` naming the params that edit content. Angle and story changes still go back through niche_angle_propose; they invalidate the verifier trust block and need fresh generation. Response includes a `diff[]` array listing every field that changed (`{field, before, after}`) so agents can show users the delta rather than the full new payload.

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• get_document

  redm-mcp

  Fetch full markdown of a doc by `path` (as returned by `browse`, `semantic_search`, or `grep_docs`). Use to retrieve full content after a search snippet looks promising. Pass `heading` (full breadcrumb like `Character Management > Inventory Management`, or just the leaf — case-insensitive, fuzzy) to fetch only that section. Deep-heading matches auto-prepend the H2 parent's intro for context. For individual script natives prefer `lookup_native`. The largest rdr3_discoveries lua data tables are keyed catalogs: call with no `heading` to list their top-level keys, then pass a key as `heading` to fetch that one entry; use `grep_docs` to search values inside. For code symbols (`addItem`) use `grep_docs`. Community findings use `learning:N` paths, not `learnings/<slug>.md`. On 404 returns available headings + cross-file hints.

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• grep_docs

  redm-mcp

  Find an EXACT literal token in raw doc files (markdown + lua). Use for specific weapon/ped/animation/prop/interior/zone names (`weapon_pistol_volcanic`, `a_c_bear_01`, `p_campfire01x`), known hashes (`0x020D13FF`), walkstyles/clipsets (`MP_Style_Casual`, `mech_loco_m@`), or any string you'd `grep` for. NOT for behavior/concept queries (use `semantic_search`) or script-native hash/name lookup (use `lookup_native`). REQUIRED for tokens inside the largest rdr3_discoveries data tables (audio_banks, ingameanims_list, cloth_drawable, cloth_hash_names, object_list, megadictanims, entity_extensions, imaps_with_coords, propsets_list, vehicle_bones) — only preview-indexed for embeddings, so `semantic_search` will NOT find tokens in them. Optional: `contextBefore`/`contextAfter` for ±N surrounding lines (saves a follow-up `get_document` call); `filesOnly: true` to get paths only (cheap exploration); `multiline: true` for cross-line patterns (`(?s)foo.*bar`). Pattern uses Rust regex syntax (rg engine). PREFER one targeted call over giant `a|b|c|d|e` alternations — split into separate calls; alternations rarely improve recall and bloat the regex automaton. Returns matched lines with path + line number. Long matched lines are windowed ±60 chars around the match (…); to read around a hit, use `read_lines({path, start})` for the preview-only mega-tables listed above (get_document holds only their ~80-line head), or `get_document({path})` for ordinary docs. If you are retrying after a previous pattern returned no matches, populate `prior_attempt` so the server can record what didn't work and steer alternative spellings.

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• decoder_intelligence

  Heista

  Browse individual decoded ads from Heista's corpus of real winning Meta/TikTok creative. Takes optional filters: vertical, creative_format, marketing_angle, hook_type, algo_intent, brand (partial name match), and limit (1-10, default 5). Each result returns beat timeline, classification, psychology, runtime performance signals (active days on Meta when available), and a decode id you can pass into generate_adscript with source_type="decode" to write a fresh script on that exact structure. Free, read-only, idempotent — no credits consumed. Use this when the user wants a specific ad as a script template (not an averaged formula), asks "show me winning ads in [vertical]", "what are [brand]'s top ads", or wants to see examples before committing to a generation. Source discovery surface — the response is the spine; for the full bundle with transcripts and director's read, call get_decode by id afterwards. Do NOT use to decode a NEW ad from a URL — use decode_ad (paid). Do NOT use for category-level patterns abstracted across multiple ads — use adformula_intelligence. Do NOT use to write the script itself — use generate_adscript or write directly from the bundle.

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• generate_adscript

  Heista

  Generate direct-response video ad scripts by fusing a proven structural source (decoded ad or formula) with a brand's PowerSource. Output is feed-native ad copy for paid social (Meta, TikTok, Reels) in the brand's voice — hook, beat-by-beat body, CTA close, plus visual direction per beat. Takes source_id (from adformula_intelligence, decoder_intelligence, or decode_ad), source_type ("formula" or "decode"), powersource_id (from any create_powersource_*), and tunable params: count (1-5 variants, tensions and selling points auto-rotated across variants), script_mode ("blueprint" preserves source structure exactly, "remix" preserves psychology but writes original copy), duration (target seconds), audience, tension override, selling_points override, voice_mode ("creator" for UGC default, "brand" for owned channels), and idempotency_key. Use this when the user says "write me a script", "I need a TikTok script", "write an ad based on this", or wants shell-faithful replication of a proven winner in their own brand voice. REQUIRES both a structural source AND a powersource — guide the user through creating either if missing. Metered pricing — typically 2-5 credits per script (~2 credits for 15s, ~5 credits for 60s). Pre-flight reserves a 17-credit ceiling and refunds the difference after measurement. Do NOT use to discover sources — use decoder_intelligence or adformula_intelligence first. Do NOT use to extract brand intel — use create_powersource_url first.

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• set_param

  kernelcad

  Use this when you need to edit a param() default value in a kernelCAD script. Returns the modified code as text plus diagnostics from re-evaluating the result. Caller persists the new code via standard file-write tools (this tool has no side effects).

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• create_product

  KernelScan

  Create a new product, run analysis, and return its initial stats. ``config_upload_id`` references a previously-staged .config that the caller POSTed to ``/api/configs/uploads`` over plain HTTP — the LLM does NOT emit the config text itself (a real kernel .config is ~100–200 KB and exceeds a single tool-call output budget). Workflow: 1. Caller / wrapper script: ``curl -H "Authorization: Bearer ks_live_..." \ -F "config_file=@.config" \ https://kernelscan.io/api/configs/uploads`` returns ``{config_upload_id, sha256, size_bytes, expires_at}``. 2. Pass that ``config_upload_id`` into this tool. Uploads are per-user, single-use, and expire 30 minutes after upload. Same gates as POST /api/products: free can't create products; paid plans are capped at their resolved product limit — read it (and any per-account override) from ``whoami.product_limit`` rather than assuming a fixed per-tier number. ``factor_ids`` are silently ignored unless the plan allows security factors (``whoami.can_use_factors``). Re-using a product name returns 409. Creating a product RUNS an analysis, so it spends one unit of the team's SHARED monthly analysis allowance (``whoami.monthly_analyses_used`` / ``monthly_analyses_limit``). When the allowance is exhausted the tool fails with "Monthly analysis limit reached (…/month) [429]". This is a durable monthly quota — NOT the transient per-call rate limit that also surfaces as 429: it will not clear until next month, so report it to the user instead of retrying. Check ``whoami`` before a batch of creates.

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• entry.detail

  HeyClaude — Claude & AI workflow directory

  Fetch a read-only HeyClaude registry entry detail payload by category and slug. By default (bodyMode='excerpt') the body markdown is trimmed to a short lead and large copyable fields are omitted to conserve context, with bodyChars/bodyTruncated/omittedFields describing what was dropped; pass bodyMode='full' for the complete content or 'none' to drop the body entirely. Use entry.asset to retrieve omitted install/script content.

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• generate_clips

  Recao

  Render UGC video scenes as ad-ready clips, metered per second of video (the estimate shows the exact price before anything renders). Pass 3 to 6 scenes (5 to 8 seconds each, one action per scene, spoken lines at most 20 words; empty spoken_line for silent characters). Consecutive scenes pack into single TAKES of up to 15 seconds, one generation each. HOW CHARACTER IDENTITY WORKS, read carefully: all characters are described in TEXT (avatar_id resolves to its persona brief; or write the persona field yourself, covering one character or a whole ensemble). The video model rejects every image that contains a person, so no photo can anchor a face. Text keeps a character IDENTICAL only WITHIN a take; ACROSS takes it preserves the look and styling but the exact face can drift, and neither avatar_id nor persona prevents that. Structure your script so scenes where the same character must be recognizably identical sit adjacent and fit one take (15s or less); treat cross-take appearances as different shots of a matching character, and review the result. reference_image_urls (up to 9 https images) keeps real products or props on-model in every take; these images must contain no people. Without confirm, it validates the contract and returns the per-scene price estimate in EUR, and makes nothing. With confirm=true it starts the metered render and returns a job_id: rendering runs in the background over a few minutes, so poll clips_status with that id to get per-scene clip URLs plus the uncut takes. Paid plans only.

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