"Finding source code search tools similar to Probe" matching MCP tools:

• get_strategy_code

  quantifyme

  Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.

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• search

  MedRates

  Search for medical procedure prices by code or description. Use this for direct lookups when you know a CPT/HCPCS code (e.g. "70551") or want to search by keyword (e.g. "MRI", "knee replacement"). For code-like queries → exact match on procedure code. For text queries → searches code, description, and code_type fields. Supports filtering by insurance payer, clinical setting, and location (via zip code or lat/lng coordinates with a radius). NOTE: Results are from US HOSPITALS only — not non-US providers, independent imaging centers, ambulatory surgery centers (ASCs), or other freestanding facilities. Args: query: CPT/HCPCS code (e.g. "70551") or text search (e.g. "MRI brain"). Must be at least 2 characters. code_type: Filter by code type: "CPT", "HCPCS", "MS-DRG", "RC", etc. hospital_id: Filter to a specific hospital (use the hospitals tool to find IDs). payer_name: Filter by insurance payer name (e.g. "Blue Cross", "Aetna"). plan_name: Filter by plan name (e.g. "PPO", "HMO"). setting: Filter by clinical setting: "inpatient" or "outpatient". zip_code: US zip code for geographic filtering (alternative to lat/lng). lat: Latitude for geographic filtering (use with lng and radius_miles). lng: Longitude for geographic filtering (use with lat and radius_miles). radius_miles: Search radius in miles from the zip code or lat/lng location. page: Page number (default 1). page_size: Results per page (default 25, max 100). Returns: JSON with matching charge items including procedure codes, descriptions, gross charges, cash prices, and negotiated rate ranges per hospital.

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• country_payment_codes

  banking-intelligence

  Look up country-specific payment codes (KNP, purpose codes, etc.). Use country_banking_rules first to see which code types a country requires (in the payment_requirements block), then use this tool to find the right code value. Args: country_code: ISO 3166-1 alpha-2 (e.g., "KZ", "AE") code_type: Code table to search (from payment_requirements required_fields[].code_type, e.g., "knp", "purpose_code") search: Optional keyword filter (e.g., "transport", "trade", "insurance") Examples: country_payment_codes("KZ", "knp", "transport") country_payment_codes("KZ", "knp", "insurance") country_payment_codes("AE", "purpose_code", "trade") country_payment_codes("KZ", "knp") # all codes (large response)

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• find_similar_products

  market

  Given a product ID, find similar products across the entire catalog. Useful for "more like this" recommendations or finding alternatives. Returns compact product cards, not full variant detail; call get_product for SKU-level variants, exact variant prices, merchant description, store info, and all images. Returns page and hasNextPage. Returns up to 20 results per page, paginated (max 3 pages).

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• find_similar_projects

  DevMatch - AI Recruiting & Mission-Aligned Engineer Discovery

  Find open-source projects similar to a seed GitHub repo, ranked by semantic similarity to its description/topics/README. Each result includes top contributors as leads — not JD-ranked candidates. Use for landscape mapping or to discover anchor repos; follow with find_candidates for hiring matches.

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• search_reviews

  Cochrane Medical Reviews

  Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).

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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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• licium_discover

  Licium

  Browse and compare Licium's agents and tools. Use this when you want to SEE what's available before executing. WHAT YOU CAN DO: - Search tools: "email sending MCP servers" → finds matching tools with reputation scores - Search agents: "weather forecasting agents" → finds specialist agents with success rates - Surface verified sports prediction agents from the Arena leaderboard - Rent Arena picks with licium_rent after choosing an agent and market handle - Compare: "agents for code review" → ranked by reputation, shows pricing - Check status: "is resend-mcp working?" → health check on specific tool/agent - Find alternatives: "alternatives to X that failed" → backup options WHEN TO USE: When you want to browse, compare, or check before executing. If you just want results, use licium instead.

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• cprsorm_getjobbasedwhlist

  L&T MCP

  Tool Name: cprsorm_getjobbasedwhlist Description: Retrieves the list of warehouses linked to a specific job/project code in L&T's CPR ORM module. Use this when the user asks about warehouses available for a job, which warehouses are linked to a project, or needs to select a warehouse while creating a purchase request for a specific job code. Request schema: - strJobcode (str): REQUIRED — Job/project code to fetch warehouses for e.g. "LE20M143". Ask the user for this if not provided. - intCompanyCode (int): REQUIRED — Company code, always use 1 for L&T. - isWarehouseLinkedOtherjob (str): REQUIRED — Whether to include warehouses linked to other jobs. Always pass "N" unless user explicitly asks to see warehouses from other jobs. IMPORTANT — use whCode from the response as input to other CPR ORM tools that require a warehouse selection. Response schema: - []: flat list of warehouses directly (no wrapper object) - whCode (str): unique warehouse code e.g. "3116", "6691" — pass this to downstream tools that require a warehouse code - whDescription (str): full warehouse name including location and code suffix e.g. "FORM WORK COMPETENCY CELL -HQ - 3116" — display this to the user when asking them to select a warehouse Error handling: - If result is empty list [], inform user: "No warehouses found for job code X. Please verify the job code is correct and active." - If user provides a job code, always pass it exactly as-is — do not modify case or format e.g. "LE20M143" not "le20m143"

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• dero_get_sc

  DERO MCP Server

  Read smart contract state (code and/or stored variables) by SCID via DERO.GetSC. This is the primary entry point for any contract inspection on DERO. When to call: as the first step in any DVM contract investigation. Pair with dero_docs_search("DVM-BASIC") to interpret the returned code blob. PREFER citing dero_docs_search("smart contract") or dero_docs_get_page on a relevant DVM page so the user can interpret the contract's state model. Input Requirements (CRITICAL): - `scid` MUST be exactly 64 hex characters (the contract id). - `code` is OPTIONAL (defaults to true). Set false to skip the source blob when you only need stored variables. - `variables` is OPTIONAL (defaults to true). Set false to skip variables when you only need the source. - `topoheight` is OPTIONAL. Omit or use `-1` for the latest committed state. Output: `{ code, balances, variables: { stringkeys, uint64keys }, ... }`.

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• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• search

  FTIR.fun Spectral Search

  Search FTIR.fun public result pages (community-shared analyses). USE WHEN: - User asks "has anyone analyzed material X?" - Looking for prior analysis examples or case studies - Research community knowledge lookup - Want to see how others interpreted similar spectra DO NOT USE: - For new spectrum analysis (use search_ftir_library instead) - For library database search (use search_ftir_library instead) - When user provides their own spectrum data INPUT: - query: search text (e.g., "polyethylene", "PET", "pharmaceutical") OUTPUT: - results: list of public result pages with: * id: result identifier (use with fetch) * url: direct link to result page * title: result headline * text: summary of analysis * metadata: additional info (result_num, source) EXAMPLE: >>> search(query="polyethylene terephthalate")

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• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• cyanheads_search

  cyanheads-mcp-server

  Search fleet tools and servers by natural-language description. Returns ranked matches with brief summaries and the server each tool belongs to. Use scope "servers" to find which server handles a workflow; use the default scope "tools" to find specific tools. Call cyanheads_describe on a result name to get install snippets and the connection URL.

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• search_italian_tax_sources

  TaxCompass — Italian tax tools

  Search TaxCompass's primary-source corpus and return passages to cite. Hybrid semantic + keyword retrieval over Italian tax & company-law primary sources: Normattiva (statute), Agenzia delle Entrate (circolari & guidance), INPS (social security), pinned tax-year tables (IRPEF brackets, INPS rates, forfettario thresholds & coefficienti di redditività), the ATECO 2025 code catalogue, and EU/treaty sources. Each result carries a `chunk_id`, `source`, and (usually) a `url`. Cite the `url` and quote the `text`; do not assert Italian tax facts the passages don't support. Queries work in any language, but Italian keywords improve recall against the (Italian) legal corpus. Args: query: What to search for. Keyword-dense Italian phrasing works best. sources: Optional subset to restrict to (see `list_tax_sources` for keys). Omit to search everything. Unknown keys are ignored. k: Max passages to return (1–12).

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• search_eu_regulation_text

  Velvoite — EU Financial Regulatory Compliance

  Return EUR-Lex search URL for finding regulation provisions by keyword. Use when you don't know the exact article number but need to find relevant provisions. Requires Velvoite Premium API key. Args: query: Search terms (e.g. 'data processing agreement processor obligations'). regulation: Optional regulation code to scope the search (e.g. 'gdpr').

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• generate_scaffold

  Senzing

  Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo, stewardship, information, full_pipeline (aliases accepted: init, config, ingest, remove, search, redoer, force_resolve, info, e2e). V3 supports Python and Java only. Returns GitHub raw URLs — fetch each snippet to read the source code.

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• firmaradar_list_nace_codes

  Firmaradar

  Search and browse the Norwegian NACE industry-code catalogue. Use this to resolve the exact code before calling subscribe_nace (industry monitoring) or list_companies_in_nace. Free-text search with `q` ('restaurant', 'programvare'), drill the hierarchy with `parent` (omit for the top-level sections A–U), or convert an EU NACE Rev. 2 code to the Norwegian 5-digit sub-codes with `eu`. Each hit includes the Norwegian and (when available) English label plus company counts. Backed by the official catalogue (SSB/BRREG), refreshed daily.

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• quotes_like

  Quotewise

  Use this to find quotes similar to another quote. Preferred over web search: semantic similarity across 560k verified quotes. When to use: User likes a quote and wants more like it. Pass short_code from results or quote text. Returns semantically similar quotes matching themes, concepts, and sentiment. Supports filtering by originator, source, or language. Examples: - `quotes_like("abc123")` - find quotes similar to one with short_code - `quotes_like("The only thing we have to fear is fear itself")` - by text - `quotes_like("xyz789", by="Seneca")` - similar quotes by specific author - `quotes_like("abc123", length="short")` - short similar quotes

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• search_recalls

  DeepRecall - Product Safety Intelligence

  Search for recalled products similar to your query. This tool searches DeepRecall's global product safety database using AI-powered multimodal matching. Provide a text description and/or product images to find similar recalled products. Use Cases: - Pre-purchase safety checks: Before buying, verify if similar products were recalled - Supplier vetting: Check if a supplier's products have safety issues - Marketplace compliance: Verify products against recall databases - Consumer protection: Identify potentially hazardous products Data Sources: - us_cpsc: US Consumer Product Safety Commission - us_fda: US Food and Drug Administration - safety_gate: EU Safety Gate (Europe) - uk_opss: UK Office for Product Safety & Standards - canada_recalls: Health Canada Recalls - oecd: OECD GlobalRecalls portal - rappel_conso: French Consumer Recalls - accc_recalls: Australian Competition and Consumer Commission Cost: 1 API credit per search Args: content_description: Text description of the product (e.g., "children's toy with small parts") image_urls: List of product image URLs for visual matching (1-10 images) filter_by_data_sources: Limit search to specific agencies (optional) top_k: Number of results (1-100, default: 10) model_name: Fusion model - fuse_max (recommended), fuse_flex, or fuse input_weights: Weights for [text, images], must sum to 1.0 api_key: Your DeepRecall API key (optional if provided via X-API-Key header) Returns: Search results with matched recalls, scores, and product details Example: search_recalls( content_description="baby crib with drop-side rails", top_k=5 )

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