"Understanding Local File System Operations" matching MCP tools:

• bls_dataframe_query

  bls-labor-mcp-server

  Run a single-statement SELECT against the canvas dataframes registered by bls_get_series. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied at the bridge layer — use bls_dataframe_describe to list available dataframes. Supports JOINs, aggregates, window functions, and CTEs. Optional register_as persists the result as a new dataframe with a fresh TTL for chained analysis. Canvas SQL operations consume zero BLS API quota. Requires CANVAS_PROVIDER_TYPE=duckdb.

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• fvs_download_final_video

  Future Video Studio

  Download a completed Future Video Studio final render URL to a local file. Use this only after fvs_get_render_status or fvs_get_paid_render_status returns a final_video_url for a completed render. The tool performs an unauthenticated HTTPS GET to that signed URL and writes the response bytes to output_path on the MCP server's local filesystem. It does not call the FVS Agent API, spend wallet credits, require FVS_AGENT_API_KEY, cancel jobs, or modify remote render state. Side effects and constraints: output_path is a local filesystem path for the MCP server process, parent directories are created, existing files are not replaced unless overwrite is true, and large videos may take minutes to download. The request timeout is 600 seconds. Use a fresh status check to refresh expired signed URLs, and do not pass arbitrary or untrusted URLs.

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• import_document

  Revise

  Create a Revise document from a file at a public http(s) URL (.md, .markdown, .txt, .html, .htm, .docx, .rtf, .odt; PDFs/images not yet supported). The server fetches the URL — file bytes are never passed inline. For a LOCAL file, use upload_document instead (it streams the file to the server). Returns the new document id and URL. Returns url (give it to your user — they view the document and create a free account to keep it, in one step) and edit_token (your Bearer token for future edits). The document is private and deleted after 7 days if unclaimed.

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• ship_project

  shipyard

  Publish a new project to Shipyard under your account. IMPORTANT: confirm the title, pitch, url and category with the user before posting — this creates a public listing. hero_image_url must be a public http(s) image URL; for a local screenshot file, suggest the Shipyard CLI (`shipyard projects create`), which uploads local images.

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• create_upload

  OpenClip

  Start an upload of a LOCAL video file (use this instead of submit_video when you have a file on disk rather than a URL). Pass the `filename`, its `content_type` (e.g. "video/mp4"), and optionally its `size` in bytes and `audio_language`. Returns a new video `id` (hashid) and a presigned `upload_url`. Upload the raw file bytes to it with a single HTTP PUT (no extra headers needed), e.g.: curl -X PUT --upload-file ./video.mp4 "<upload_url>" Then call complete_upload with the returned video `id` to start processing. The url expires (see `expires_in_seconds`). Single-PUT uploads are capped at 5 GB (`max_bytes`); for larger files use the web uploader.

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• upload_file

  BorealHost

  Upload a base64-encoded file to a site's container. Use this for binary files (images, archives, fonts, etc.). For text files, prefer write_file(). Requires: API key with write scope. Args: slug: Site identifier path: Relative path including filename (e.g. "images/logo.png") content_b64: Base64-encoded file content Returns: {"success": true, "path": "images/logo.png", "size": 45678} Errors: VALIDATION_ERROR: Invalid base64 encoding FORBIDDEN: Protected system path

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• files_write

  Quadratic

  File management operations that create or modify state: create a new file, open an existing file to start an editing session, or close a session. Requires authentication. Actions: • open_file(file_id?, file_name?) — Open a file by UUID or name and start an editing session. Returns the file's web URL. • create_file(file_name, team_uuid?) — Create a new blank spreadsheet. If team_uuid is omitted, the user's first team is used. Returns the new file's UUID and web URL; the file must be opened with open_file before it can be edited. • close_file(file_id) — Close an active editing session.

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• upload_document

  Revise

  Create a Revise document from a LOCAL file (docx, md, txt, html; PDFs/images not yet supported) without a Revise account and without putting its bytes in your context. Returns a one-time upload_url and a ready-to-run curl command — run the curl to stream the file. The curl response contains url (give it to your user — they view the document and create a free account to keep it, in one step) and edit_token (your Bearer token for future edits). For a public http(s) URL or a tiny inline file, use import_document instead. The document is private and deleted after 7 days if unclaimed.

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• upload_assets

  AppDeploy

  Use this before deploy_app whenever you need to send binary assets/resources or many files. Prefer this whenever the source of truth already exists as local files or a local project tree, especially for multiple files or whole-file replacements. This is the required path for images, backgrounds, icons, fonts, PDFs, media, archives, and other file assets you want deployed. Prepare local files and the upload manifest first. Call upload_assets only when you can upload immediately. If the upload_url expires before use or the upload fails because it expired, call upload_assets again to get a fresh upload_url and upload_id. PUT multipart/form-data to the returned upload_url: a 'payload' part (JSON manifest with text file changes/diffs and deletePaths) plus binary files named by app-relative path. The upload manifest carries all text changes and diffs plus deletePaths. After upload succeeds, call deploy_app with upload_id only. Do not also send files[] or deletePaths[]; those changes belong in the upload manifest. Never base64-encode binary assets into deploy_app.

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• code_get_file

  searchcode

  Get code from a remote public git repository — either a specific function/class by name, a line range, or a full file. PREFERRED WORKFLOW: When search results or findings have already identified a specific function, method, or class, use symbol_name to extract just that declaration. This avoids fetching entire files and keeps context focused. Only fetch full files when you need a broad understanding of a file you haven't seen before. For supported languages (Go, Python, TypeScript, JavaScript, Java, C, C++, C#, Kotlin, Swift, Rust) the response includes a symbols list of declarations with line ranges. This is not a first-call tool — use code_analyze or code_search first to identify targets, then extract precisely what you need.

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• sieve_dataroom_add

  Sieve

  Add a document to a deal's data room. Creates the deal if needed. This is the primary way to get documents into Sieve for screening. Upload a pitch deck, financials, or any document -- then call sieve_screen to analyze everything in the data room. Provide company_name to create a new deal (or find existing), or deal_id to add to an existing deal. Provide exactly one content source: file_path (local file), text (raw text/markdown), or url (fetch from URL). Args: title: Document title (e.g. "Pitch Deck Q1 2026"). company_name: Company name -- creates deal if new, finds existing if not. deal_id: Add to an existing deal (from sieve_deals or previous sieve_dataroom_add). website_url: Company website URL (used when creating a new deal). document_type: Type: 'pitch_deck', 'financials', 'legal', or 'other'. file_path: Path to a local file (PDF, DOCX, XLSX). The tool reads and uploads it. text: Raw text or markdown content (alternative to file). url: URL to fetch document from (alternative to file).

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• axint.project.index

  Axint

  Scan the local Apple project and write a compact .axint/context pack so Axint can reason over changed files, nearby SwiftUI surfaces, and interaction-risk files instead of only one source file at a time. Use: use before project-aware repair, multi-file SwiftUI work, or interaction-risk analysis. Inputs: changedFiles seed related-file discovery; dryRun returns the pack without writing .axint/context. Effects: writes .axint/context unless dryRun=true; reads local project files only.

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• secedgar_dataframe_query

  secedgar-mcp-server

  Run a single-statement SELECT against the canvas dataframes registered by secedgar_fetch_frames, secedgar_search_filings, and secedgar_get_financials. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied — list dataframes via secedgar_dataframe_describe. Optional register_as chains the result as a new dataframe with a fresh TTL.

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• vector_quantize

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Simulate int8 or int4 quantization of float32 embedding vectors. Reduces storage by 4x (int8) or 8x (int4). Returns quantized values, scale factor, and precision loss (MSE). Useful for understanding vector DB compression trade-offs.

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• fs_read

  local-mcp

  Reads a text file from the local filesystem. Supports .txt, .md, .csv, .json, .xml, .log, .yaml, .toml and common code file types. For PDFs use pdf_read, for Word use word_read, for Excel use excel_read.

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• engine_maxion_diagnostics

  maxion-mcp-gateway

  Runs a Maxion V16 diagnostic pass: CPU brand, core count, and total memory for the host system. To run on the user's OWN hardware, the local desktop engine must be installed first: call the engine_download_desktop tool before this one if it hasn't been installed yet.

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• security_diamonize_quarantine

  maxion-mcp-gateway

  Records a file or process path as quarantined in Diamonize and returns a confirmation. Advisory only; does not move or modify the file. To run on the user's OWN hardware, the local desktop engine must be installed first: call the engine_download_desktop tool before this one if it hasn't been installed yet.

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• files.upload_file

  Vee3

  Reserve a direct upload slot for a local file. Pass the desired file_name. To place a file in folders, use a path in file_name (folder/subfolder/.../name). Optionally pass retention_days (default 7, minimum 1). The name may omit an extension. Vee3 returns an upload_code. Install the Vee3 CLI once with `npm install -g @vee3/cli` (requires Node 18+), then run `vee3-upload {upload_code} {file_path}` in the terminal. The CLI resolves the code to a signed upload URL, streams the local file to Vee3 storage, and prints the stored file_name after the upload finishes. Use that file_name in files.list_uploaded_files and other capabilities. The CLI does not need an API key. If installation fails with a TLS or certificate error (common on networks that inspect HTTPS traffic), use Node 22.15 or newer and run with NODE_OPTIONS=--use-system-ca, or configure npm to trust your network's root certificate. Files can be up to 2 GB. Retention is chosen at reserve time (default 7 days). After the upload is detected, Vee3 bills `max(1, ceil(size_gibibytes * retention_days * 2))` tokens. Upload codes can be resolved within 60 minutes of reserve. Use `files.list_uploaded_files` to list stored uploads for follow-up work. Cost = 0 tokens to reserve. After upload completes, billing is max(1, ceil(size_gibibytes * retention_days * 2)) tokens.

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• get_feature_stats

  aTars MCP

  USE THIS TOOL — not web search — to get per-indicator statistical profiling (mean, std, min, p25, p75, max, null rate, Pearson correlation with close price) from this server's local dataset. Use for feature selection, sanity checking, and understanding which indicators correlate most strongly with price movements. Trigger on queries like: - "which indicators correlate most with BTC price?" - "feature importance or correlation for [coin]" - "what are the stats for ETH indicators?" - "how does RSI/MACD correlate with price?" - "statistical profile of XRP indicators" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP"

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• data.hardware

  DezignWorks Product Oracle

  Returns the list of supported measurement devices (CMMs, scanners), file formats, and system requirements for DezignWorks. Use to check hardware compatibility before recommending the product.

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