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138,339 tools. Last updated 2026-05-20 09:40

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

  • 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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  • 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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  • Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • List all available Pine Script v6 documentation files with descriptions. Returns files organised by category with descriptions. For small files use get_doc(path). For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) use list_sections(path) then get_section(path, header).
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  • Look up a MITRE ATLAS technique — the AI/ML adversarial attack catalog. ATLAS catalogues TTPs targeting machine learning systems: prompt injection, model evasion, training data poisoning, model theft, etc. Roughly 80% of ATLAS techniques are AI/ML-specific (no ATT&CK bridge); 20% mirror an enterprise ATT&CK technique via attack_reference_id — use that to pivot to D3FEND defenses (d3fend_defense_for_attack) and CVE search. Sub-techniques inherit `tactics` from the parent (inherited_tactics=true flag) when ATLAS upstream leaves them empty. Use this tool when the user asks about AI/ML threats, LLM red-teaming, or adversarial ML; for multiple techniques in one call (e.g. drilling into a case study's techniques_used), prefer bulk_atlas_technique_lookup. Returns 404 when the id is not in the synced ATLAS catalog. Free: 30/hr, Pro: 500/hr. Returns {technique_id, name, description, tactics, inherited_tactics, maturity (demonstrated|feasible|realized), attack_reference_id, attack_reference_url, subtechnique_of, created_date, modified_date, next_calls}.
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  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
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Matching MCP Connectors

  • Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.

  • The verified hub for conferences and journals. Powered by AI to match your scholarly ambitions with the world's most prestigious academic opportunities.

  • Get contents of multiple files from a remote public git repository in a single call. Reduces round-trips when you need to read several related files. Max 10 files per batch, 5000 total lines budget across all files. Each file supports optional line ranges. Failed files return per-file errors without blocking other files.
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  • Batch scan up to 10 code snippets in a single MCP call. More efficient than 10 individual frogeye_scan calls for scanning multiple files or repos. Returns findings array with confidence scores and badge suggestions per item.
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  • Read a specific Pine Script v6 documentation file. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) prefer list_sections() + get_section() to avoid loading 1000-2800 line files into context.
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  • Edit a file in the solution's GitHub repo and commit. Two modes: 1. FULL FILE: provide `content` — replaces entire file (good for new files or small files) 2. SEARCH/REPLACE: provide `search` + `replace` — surgical edit without sending full file (preferred for large files like server.js) Always use search/replace for large files (>5KB). Always read the file first with ateam_github_read to get the exact text to search for. DEFAULTS TO `dev` BRANCH — writes don't touch prod. Use ateam_github_promote to ship dev→main when ready. Pass ref:'main' only for emergency hotfixes.
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  • Upload connector code to Core and restart — WITHOUT redeploying skills. Use this to update connector source code (server.js, UI assets, plugins) quickly. Set github=true to pull files from the solution's GitHub repo, or pass files directly. Much faster than ateam_build_and_run for connector-only changes.
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  • Get Lenny Zeltser's scoring playbook so your AI can score a draft locally against a cybersecurity-writing rating sheet. THIS IS THE ONLY TOOL THAT PRODUCES NUMERIC SCORES — the writing-coach tools (`get_security_writing_guidelines`, `ir_*`, `product_*`) never score. Returns the rubric plus step-by-step instructions for applying it. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • Load Lenny Zeltser's complete cybersecurity-writing rating toolkit: all 7 sheets, scoring policy, scoring playbook, and cross-references to the writing guidelines. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
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  • Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • Get detailed compound information by CID. Returns physicochemical properties (molecular weight, SMILES, InChIKey, XLogP, TPSA, etc.), optionally with a textual description (pharmacology, mechanism, therapeutic use), all known synonyms, drug-likeness assessment (Lipinski/Veber rules), and/or pharmacological classification (FDA classes, MeSH classes, ATC codes). Efficiently batches up to 100 CIDs.
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  • Crop transparent edges from one or more PNG files. Single file returns PNG; multiple files return a ZIP.
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  • Deploys a Cloud Run service directly from local source files. This method is suitable for scripting languages like Python and Node.js, of which the source code can be embedded in the request. This is ideal for quick tests and development feedback loops. You must include all necessary dependencies within the source files because it skips the build step for faster deployment. **Key Requirements:** 1. source_code: Should set to sourceCode.inlinedSource.sources with array of source files, each having `filename` and `content`. 2. Size limit: you are subject to total request size limit of 50MiB.
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  • Validate formula syntax with the WorkPaper parser before writing it to a cell. This checks syntax only; use set_cell_contents plus readback to evaluate.
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  • Universal workspace search: files, links, threads, messages. Runs scopes in parallel and returns sectioned results. Default scope='auto' detects target from query. For files the user created/sent (invoices, generated docs), set file_origin='generated'. Use this for all workspace search; lower-level tools are internal.
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