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298,647 tools. Last updated 2026-07-14 15:44

"Using code execution to replace native tooling" matching MCP tools:

  • Use this when the user wants to discover the canonical marketing reporting graph, available sources, supported metrics, supported dimensions, or which connectors are live today. Each source also reports a `passthrough` field describing whether native fields beyond the curated list are accepted (GA4 accepts any native dimension/metric; Search Console accepts any native dimension; Bing is limited to the curated fields). Do not use this for GA4 account discovery or data retrieval.
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  • Resolve a RedM/RDR3 SCRIPT native by hash or name — O(1), exact. Use whenever you see `Citizen.InvokeNative(0x...)`, `Citizen.invokeNative('0x...')`, `GetHashKey('NAME')`, or a SCREAMING_SNAKE_CASE native name (e.g. `SET_ENTITY_COORDS`, `GetPedHealth`) in Lua/JS/TS. NOT for game-data hashes (weapon/ped/animation names) — use `grep_docs`. Pass `hash` (0x… optional, case-insensitive) or `name` (exact first, ILIKE substring fallback). Returns name, hash, namespace, return type, params, description, full content, plus `findings[]` — community gotchas linked to that native. Inspect `findings[].id` and call `get_document({path: 'learning:<id>'})` for full body. Also returns `refDocs[]` — enum/flag value tables for that native (the constants to pass for params like flagId/attributeIndex/eventType). When `refDocs[].content` is set, it's the inline enum table — use those values directly. When `content` is null but `refDocs[].fetch` is present, the table was too large to inline — run that exact call (e.g. `get_document({ path: "refdoc:eEventType" })`) to get the full table; `refDocs[].preview` shows the first lines. github entries (no `fetch`) are url-only.
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  • Estimate gas (compute + storage) for transfers, SC deploys, or SC invokes via DERO.GetGasEstimate. This is a PRE-FLIGHT check; nothing is submitted. When to call: BEFORE any wallet-side transfer/scinvoke (using external wallet tooling) to size fees, OR when explaining deploy costs to a user. PREFER citing dero_docs_search("gas estimate" or "fees") so the user understands how compute vs storage gas are charged. Input Requirements (CRITICAL): - At least ONE of `transfers`, `sc`, or `sc_rpc` MUST be provided. - `sc` is the DVM-BASIC contract source string when estimating a deploy. - `sc_rpc` is an array of `{ name, datatype, value }` invocation arguments (entrypoint + SC_ID + caller-provided params). - `signer` is OPTIONAL but PREFERRED; pass the `dero1.../deto1...` address that would sign the eventual tx. Output: `{ gascompute, gasstorage, status }`.
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  • Complete Disco signup using an email verification code. Call this after discovery_signup returns {"status": "verification_required"}. The user receives a 6-digit code by email — pass it here along with the same email address used in discovery_signup. Returns an API key on success. Args: email: Email address used in the discovery_signup call. code: 6-digit verification code from the email.
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  • OPTIONAL. Bind THIS agent identity to a human Zero account so they can prove they own what you build and remember, and recover you if your key is ever lost. You are fully autonomous without it -- never required to use space0. To use it: ask your human to issue a one-time owner claim code from their account at 0.space (it looks like s0c_...), then pass it here ONCE. It only works while you are unbound, and a code only ever binds you to the human who issued it. Persist your key first (see the connect instructions) -- binding complements the disk key, it does not replace it.
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  • Paid tier only. Fetch a senior-QS skill methodology by slug (see list_skills) and APPLY it to the user's documents — the returned body is the system instruction for you to run the methodology on the customer's tokens; CivilQuants does not run inference. Paid callers get the full methodology; anonymous/free callers get a TIER_INSUFFICIENT upsell body; a rejected token gets an INVALID_TOKEN re-authenticate body. The document-heavy skills assume you can chunk/parse the customer's files and render a Word pack locally — that needs a code-execution client (Claude Code / Codex / VS Code) and the pack from get_document_pipeline; on a chat connector you can still read and reason with the methodology. Sign up at https://civilquants.com/pricing. Example: get_skill(skill="tender_risk_assessment").
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Matching MCP Servers

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    Enables efficient AI agent operations through sandboxed Python code execution with progressive tool discovery, PII tokenization, and skills persistence, achieving up to 98.7% token reduction by processing data in a sandbox rather than in context.
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Matching MCP Connectors

  • AI agents publish bounties for real-world tasks. Gasless USDC payments via x402.

  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • Returns the complete setup and usage guide for SwapWizard. Call this FIRST before using any other tool. Covers: required configuration (API key, Alchemy RPC URL, private key), how to use poolId correctly, step-by-step operational flows for swap/zap in/zap out/analyze, transaction execution details, and approval rules.
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  • Patch or replace files on an existing site. Defaults to patch mode: only the listed files change; everything else stays. Pass mode:'replace' to wipe-and-replace the whole site (the legacy behaviour, surfaced explicitly so it can't happen by accident). Use `delete: [paths]` in patch mode to remove specific files without wiping the rest. Use `dryRun: true` to preview the diff before committing. LARGE FILES: a 100-250 KB text file fits in one call with encoding:'gzip+base64' (gzip locally, base64 the result) — prefer that over begin_deploy + add_file_chunk streaming. Errors if the site does not exist.
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  • Get hourly aggregated token flows for a specific segment of holders over a date range. The segments are Top 100 holders, Whale, Public Figure, Smart Money and Exchange. **Note:** Using `holder_segment: smart_money` is not a good proxy for an overall market view. Use it only if user explicitly requests it, or to combine it with other non smart money data. This is a **more granular** tool than `token_recent_flows_summary` and provides the TOTAL flows over the entire time frame broken down by segment. **Modes:** - `onchain_tokens` (default): Analyze on-chain tokens by contract address - `perps`: Analyze Hyperliquid perpetual futures by symbol (chain auto-set to "hyperliquid") — supports native tokens **NOTE:** This tool does not support native tokens (so11111111111111111111111111111111111111112, 0xeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee) in `onchain_tokens` mode. Native tokens (by symbol - SOL, ETH, ARB etc) ARE fully supported in `perps` mode.
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  • Get hourly aggregated token flows for a specific segment of holders over a date range. The segments are Top 100 holders, Whale, Public Figure, Smart Money and Exchange. **Note:** Using `holder_segment: smart_money` is not a good proxy for an overall market view. Use it only if user explicitly requests it, or to combine it with other non smart money data. This is a **more granular** tool than `token_recent_flows_summary` and provides the TOTAL flows over the entire time frame broken down by segment. **Modes:** - `onchain_tokens` (default): Analyze on-chain tokens by contract address - `perps`: Analyze Hyperliquid perpetual futures by symbol (chain auto-set to "hyperliquid") — supports native tokens **NOTE:** This tool does not support native tokens (so11111111111111111111111111111111111111112, 0xeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee) in `onchain_tokens` mode. Native tokens (by symbol - SOL, ETH, ARB etc) ARE fully supported in `perps` mode.
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  • Compile TypeScript source (defineIntent() call) into native Swift App Intent code. Returns { swift, infoPlist?, entitlements? } as a string — no files written, no network requests. On validation failure, returns diagnostics... Use: use when TypeScript DSL source should become Swift; use validate for cheaper preflight only. Effects: read-only generated Swift/diagnostics; writes no files and uses no network.
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  • List the 22 chapters of CID-10 with their code ranges and Portuguese titles. Use this tool to: - See the top-level structure of CID-10 (chapters I-XXII, e.g., "I. Algumas doenças infecciosas e parasitárias", "IX. Doenças do aparelho circulatório") - Map a code to its chapter by code range (e.g., I00-I99 → chapter IX) - Build a navigable table of contents for downstream tooling Returns 22 entries — CID-10 V2008 has not been updated since 2008.
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  • Obtain the CivilQuants customer-side document pipeline — the toolkit the document-heavy skills (tender review, geotechnical / geo-environmental interpretation) use to chunk a tender pack and render a Word pack on the user's machine. Returns the self-unpacking chunking package, the pipeline discipline, and the python-docx render helpers. Universal (free + paid). NOTE: running the pipeline over real documents requires a code-execution client (Claude Code / Codex / VS Code) — a chat connector can read the toolkit but cannot execute it. The full kit is large (~60 KB); pass component='chunking'|'discipline'|'render' for one part (~20 KB each), or omit it for the whole kit.
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  • Returns the complete setup and usage guide for SwapWizard. Call this FIRST before using any other tool. Covers: required configuration (API key, Alchemy RPC URL, private key), how to use poolId correctly, step-by-step operational flows for swap/zap in/zap out/analyze, transaction execution details, and approval rules.
    Connector
  • Full map of one GTM category — leaders, runner-ups, and skip/replace candidates. Returns every catalogued tool in the bucket with cost, AI-readiness, swap-registry status, and partner sign-up links. Use when the user wants to see the full landscape for a category (e.g. 'show me all CRMs', 'what outbound tools exist', 'map the analytics category') — strictly more comprehensive than `recommend_partner` (single best pick). Known buckets: crm, outbound, data, marketing-automation, analytics, meetings, support, scheduling, automation, seo, cdp, revenue-intelligence, chat, collaboration, phone, landing-pages, linkedin, ai-content, saas-mgmt, enablement, ai-tooling.
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  • The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.
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  • Add a new contact for the user. A verification code (OTP) will be sent to the contact address. The user must verify the contact using openmandate_verify_contact before it can be used on mandates. The first contact added becomes the primary contact automatically.
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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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  • POST a PxWeb query to a MakStat (North Macedonia statistics) table and return observations as json-stat2. body must be {query:[{code, selection:{filter,values}}], response:{format:'json-stat2'}}. PxWeb enforces a cell-count limit — narrow each dimension's values using codes from table_meta to avoid rejection.
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  • List the 10 senior-QS skill methodologies CivilQuants exposes (tender review, risk assessment, QS measurement/contract advice, geotechnical + geo-environmental interpretation, earthworks, preliminaries, pavement design, subcontract analysis). Universal discovery — both tiers see the full list. Returns each skill's slug, title, one-line summary and tier; then call get_skill(skill=<slug>) to fetch the methodology body. The skills are paid-tier; a free caller gets a sign-up prompt from get_skill. NOTE: the document-heavy skills (tender review, the interpretation skills) need a code-execution client (Claude Code / Codex / VS Code) plus the chunking pack from get_document_pipeline to run a real tender pack — on a chat connector you can read the methodology but cannot chunk/parse files.
    Connector