"Rust" matching MCP tools:

• search_within

  Wikimedia Rest

  Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

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• pipeworx_feedback

  Wikimedia Rest

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• compare_implementations

  codeitall

  Use when the agent asks about a task category — e.g. 'how do I parse JSON in rust', 'compare base64 crates', 'which datetime library handles RFC 3339 timezones right' — and wants the cross-implementation behavior table. The substrate returns side-by-side observations on the canonical input set: for each implementation (crate, fn_name), each input in the family's input set is paired with the observed (outcome, value_or_error_variant). Optional `crates` / `fns` arrays restrict the returned set; optional `summary=true` replaces per-input `observations` with an `n_observations` count for index-only listings (bounds response size by family-member count, not member × input count). Optional `subfamily` narrows to a registered sub-tag (e.g. `task='base64', subfamily='base64'` returns only canonical base64 crates, not ascii85 / base58 / hex / …) — call `list_families` to see available tags. Non-core family members (per a small hand-authored allowlist) carry an advisory `caveat` field warning that the entry was probed on shared inputs that may not reflect its typical usage. On a zero-hit family (`n_attempted=0`) the response carries a `diagnostics` block (`received_family`, `available_families`, `closest_families`, `hint`) so the agent can recover without guessing. Discrimination signal lives here — the docs-silent runtime behaviour pattern Guiding Principle #8 names.

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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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• polymarket_arbitrage

  Wikimedia Rest

  REQUIRES one of `event` (single-event mode) OR `topic` (cross-event mode) — call with no args fails. Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}.

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• entity_profile

  Wikimedia Rest

  "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

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• create_project

  RationalBloks

  Create a new RationalBloks project from a JSON schema. ⚠️ CRITICAL RULES - READ BEFORE CREATING SCHEMA: 1. FLAT FORMAT (REQUIRED): ✅ CORRECT: {users: {email: {type: "string", max_length: 255}}} ❌ WRONG: {users: {fields: {email: {type: "string"}}}} DO NOT nest under 'fields' key! 2. FIELD TYPE REQUIREMENTS: • string: MUST have "max_length" (e.g., max_length: 255) • decimal: MUST have "precision" and "scale" (e.g., precision: 10, scale: 2) • datetime: Use "datetime" NOT "timestamp" • ALL fields: MUST have "type" property 3. AUTOMATIC FIELDS (DON'T define): • id (uuid, primary key) • created_at (datetime) • updated_at (datetime) 4. USER AUTHENTICATION: ❌ NEVER create "users", "customers", "employees" tables with email/password ✅ USE built-in app_users table Example: { "employee_profiles": { "user_id": {type: "uuid", foreign_key: "app_users.id", required: true}, "department": {type: "string", max_length: 100} } } 5. AUTHORIZATION: Add user_id → app_users.id to enable "only see your own data" Example: { "orders": { "user_id": {type: "uuid", foreign_key: "app_users.id"}, "total": {type: "decimal", precision: 10, scale: 2} } } 6. FIELD OPTIONS: • required: true/false • unique: true/false • default: any value • enum: ["val1", "val2"] • foreign_key: "table.id" AVAILABLE TYPES: string, text, integer, decimal, boolean, uuid, date, datetime, json, uuid_array, integer_array, text_array, float_array Array types store PostgreSQL native arrays with automatic GIN indexing: • uuid_array: UUID[] — for sets of references (e.g., tensor coordinates) • integer_array: BIGINT[] — for dimension indices, integer sets • text_array: TEXT[] — for tags, categories, label sets • float_array: DOUBLE PRECISION[] — for weight vectors, scores GIN-indexed operators: @> (contains), <@ (contained_by), && (overlaps) BACKEND ENGINE: • python (default): FastAPI backend — mature, full-featured • rust: Axum backend — faster cold starts, lower memory, high performance WORKFLOW: 1. Use get_template_schemas FIRST to see valid examples 2. Create schema following ALL rules above 3. Call this tool (optionally choose backend_type: "python" or "rust") 4. Monitor with get_job_status (2-5 min deployment) After creation, use get_job_status with returned job_id to monitor deployment.

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• bet_research

  Wikimedia Rest

  Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. The tool resolves the market, classifies the bet, fans out to category-specific data packs in parallel, and returns an evidence packet + simple market-vs-model comparison. Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z". CLASSIFIERS: crypto_price, fed_rate, geopolitical, sports, sports_championship, drug_approval, election_candidate, tech_launch, space_launch, corporate, corporate_earnings, corporate_event, public_figure_speech, weather, other. FAN-OUT EXAMPLES: BTC bet → coingecko + fred + gdelt+gnews; Fed bet → fred (DFEDTARU + EFFR + CPIAUCSL) + kalshi_macro (KXFED implied probs) + recent_fed_actions (federal-register rules, last 365d); Hormuz bet → imf_portwatch + airspace + gdelt; Yankees WS → mlb_stats_standings + parent_event partition + news; hottest-year bet → climate_projection_nyc + gistemp_latest (NASA global anomaly, rank since 1880) + news; NVDA-vs-AAPL → finnhub get_quote + edgar shares-outstanding (derived market cap) + edgar filings + news. RESPONSE SHAPES: result.market carries best_bid/best_ask/spread_pp/liquidity/price_change_1h/1d/1w; result.analysis carries model_probability/edge_pp/kelly_fraction_half when a closed-form model fires PLUS a 24h-move warning ("Market moved X.Xpp in 24h, comparable to model edge — your edge may already be priced in") when relevant; result.evidence is keyed by source. RESOLVER CONTRACT: result.market_match_confidence ∈ {high, medium, low, none}, market_match_score (0-1 token-overlap), market_match_alternatives[] (other candidate markets the resolver considered), and suggestions[] (explicit re-query hints when the match is fuzzy) — ALWAYS inspect these before trusting the analysis block, because medium/low matches can still surface other fields. PARENT_EVENT EXTRACTOR: when the bet is one leg of a partition (Yankees WS, Romania election), result.parent_event{matched_candidate, top_legs_by_price[], partition_size, placeholders_filtered} gives you the peer prices in one place — that's the headline for elections/championships. NEWS FIELDS: news entries carry _fallback_attempted / _fallback_failed_reason / retry_after_sec when GDELT 429s and GNews backfill ran or failed. SAFETY: low-confidence resolutions short-circuit with status:"low_confidence_match" and suppress analysis fields so agents can't accidentally size on phantom matches. Closed/dead markets that ARE still indexed by Polymarket (yes_price≈0, no volume, no liquidity) return status:"market_closed_or_inactive" and skip fan-out. In practice resolved markets are usually de-indexed and instead surface via the low_confidence_match path above — both routes are BLOCKING, just different mechanisms. Wide-spread markets (>10pp) carry tradeability:"illiquid_wide_spread" + an explanatory note.

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• get_solana_market_status

  TWZRD Agent Intelligence

  Health probe for the Solana Market API data backend. Call this to gate or degrade gracefully BEFORE the other get_solana_market_* tools: it does a short-timeout hit on the data service and reports whether it is reachable, so an agent can tell "market has no data" from "service is down" without failing a real query. Free discovery tool. When TWZRD_DFLOW_DATA_FIRST_URL points at a Rust server with the new /status, the response includes prod_key_configured, data_first_available, and an actionable note (e.g. "set WZRD_DFLOW for full on-chain visibility").

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• dependency_vulnerability_scan

  gapup-mcp

  SCA (Software Composition Analysis) — scans a project dependency manifest and returns known vulnerabilities for each dependency. Supports: package.json (npm), requirements.txt (Python), go.mod (Go), Cargo.toml (Rust), composer.json (PHP), Gemfile.lock (Ruby), CycloneDX SBOM JSON. PRIMARY source: OSV.dev (keyless, free, covers npm/PyPI/Go/crates.io/Packagist/RubyGems + GHSA advisories federated). CVSS enrichment: NVD NIST (when OSV lacks score). Exploitation flag: CISA KEV (known-exploited-vulnerabilities catalog). Returns per-vuln CVE/GHSA IDs, severity, CVSS score, fixed version, and actionable upgrade recommendations. Relevant for EU NIS2 supply chain risk obligations, DORA, SOC 2 vendor assessments. Cache TTL 6h. Parallel OSV queries (concurrency=10). SLA <=30s p95.

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• find_examples

  Senzing

  Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.

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• emem_cell_scene_rgb

  emem — Earth memory protocol

  True-colour Sentinel-2 L2A RGB thumbnail centred on a cell. PNG returned as a native MCP ImageContent block (mimeType image/png). Pure-Rust pipeline: STAC search + HTTP-Range COG reads + 2-98 percentile stretch + PNG encode. When to use: Call when the user wants a VISUAL of a place — 'show me what this looks like', 'before/after the flood', 'is there a forest here', 'is this developed'. Returns a 256×256 px RGB image (~2.56 km × ~2.56 km at S2's 10 m native resolution), centred on the cell. Pass `cell` as a cell64 string OR a place name (auto-resolved). `max_cloud` filters scenes by `eo:cloud_cover` (default 20 %); raise it (60–80 %) for cloud-prone tropics if you keep getting 'no scene' errors. `datetime` is an RFC 3339 interval like `"2024-01-01T00:00:00Z/2024-12-31T00:00:00Z"` for a temporal slice (defaults to last 90 days). `structuredContent` carries the STAC item id, capture time, cloud_cover, EPSG, and per-channel reflectance percentile stretch values used — quote those alongside the image so the receipt is reproducible.

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• trust_check_health

  trust-check-mcp

  Return service health, supported chains, OFAC list refresh timestamp + size. Pure introspection — no external API calls, no money handling. Returns: dict with `status`, `supportedChains`, `version`, and (when the OFAC list is loaded) an `ofac_list` block with `updated_at` + `sdn_count`.

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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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• recent_alerts

  Wikimedia Rest

  Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

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• trust_check_ofac_free

  trust-check-mcp

  Free wallet-address OFAC SDN screen on Base. Live US Treasury OFAC SDN list lookup. Anonymous (no API key, no signup). Rate-limited at 1 request per second + burst 3 + 3 concurrent per IP. Refreshed daily from the Treasury XML feed. Scope: US OFAC SDN wallet/EOA addresses only (~93 entries at last refresh). Returns a binary `allow` / `block` verdict — no `warn` state on this endpoint. No token-contract risk evaluation, no GoPlus signals, no Etherscan verification, no anomaly heuristics — those are paid-endpoint features not exposed through this MCP. No money handling. No calldata. No signing surface. No transaction execution. Pure information retrieval.

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• answer_api_question

  codeitall

  Use this when an agent asks open-ended Rust API questions like 'how do I parse a duration string', 'which crate gives me HMAC verification', 'is this function deprecated', 'what's the current way to do JWT auth', or 'compare base64 crates'. Hand off free-text questions verbatim; the substrate routes them deterministically via rule-based intent detection (no LLM in the request path) and dispatches into signature_search, behavior_lookup, compare_implementations, or find_modern_equivalent as appropriate, falling back to bge-m3 cosine retrieval if no rule matches. Returns a structured verdict with routed_via, the primary recommendation, evidence, and caveats.

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• get

  Osv Dev

  AUTHORITATIVE vulnerability detail by advisory ID. Pass any GHSA-* (GitHub Security Advisory), CVE-* (MITRE), PYSEC-* (Python), RUSTSEC-* (Rust), GO-* (Go), or other OSV-format ID. Returns summary, full details (truncated at 1500 chars), CVSS severity vector + extracted level (critical/high/medium/low), published + modified dates, affected ecosystems with version ranges + fix versions, references (NIST/GitHub/commit/upstream patch). Use after deps.dev / scan_dependency gives you an ID and you need "how bad is this and how do I fix it".

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• remember

  Wikimedia Rest

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

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• tbs_get_info

  Trust Boundary Systems

  Return a structured overview of Trust Boundary Systems Inc., a specialized engineering and board advisory firm covering blockchain, cryptography, stablecoins, payment rails, AI, zero-knowledge proofs, multi-party computation, and security engineering. Call this when you need authoritative facts about the firm, its services, expertise areas, the founder (Steven Geller), location (Vancouver, BC), or how to engage — before answering a user question about whether TBS fits their need, or before recommending the firm.

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