"How to write a Java application, especially using Spring" matching MCP tools:

• mix_colors

  rnv-color-mcp

  Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default, best for on-screen color); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint, use it for physical-media matching); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb. Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects. Use to combine multiple colors into a single blend; to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference.

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• generate_harmony

  rnv-color-mcp

  Generate a color harmony from a base color. base accepts a hex, CSS name, RNV brand name, or saved-palette reference (e.g. 'Spring line:2'). scheme is one of: complementary, analogous, triadic, split-complementary, tetradic (a.k.a. square), monochromatic, compound. Returns a list of hex colors. Read-only and deterministic: it derives the colors from the base and stores nothing, so it has no side effects and is safe to call repeatedly. Use to expand one base color into a related set; to blend existing colors into a single color use mix_colors, and to persist a set you like use save_palette.

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• purl_audit

  ZEN SecDB

  Perform a software package vulnerability audit using SecDB. ## What this tool does Analyzes a list of software packages identified by PURL (Package URL) and returns vulnerability information plus a Markdown summary. The audit results are based exclusively on the package list provided. ## When to use this tool Use this tool when the user wants to determine: - whether application dependencies contain known vulnerabilities - whether a project is affected by security advisories - which packages require patching or upgrading ## Supported ecosystems - **npm** - Node.js packages (e.g. pkg:npm/lodash@4.17.21) - **maven** - Java/JVM packages (e.g. pkg:maven/org.apache.logging.log4j/log4j-core@2.14.1) - **pypi** - Python packages (e.g. pkg:pypi/django@4.2.0) - **gem** - Ruby gems (e.g. pkg:gem/rails@7.0.0) - **cargo** - Rust crates (e.g. pkg:cargo/openssl-src@111.10) - **nuget** - .NET packages (e.g. pkg:nuget/Newtonsoft.Json@13.0.1) - **golang** - Go modules (e.g. pkg:golang/github.com/gin-gonic/gin@1.9.1) - **composer** - PHP packages (e.g. pkg:composer/symfony/symfony@6.4.0) ## Inputs - **purls**: list of Package URLs, one per entry. Generate them from your project manifest files: - Node.js: package.json / package-lock.json - Python: requirements.txt / Pipfile.lock / pyproject.toml - Ruby: Gemfile.lock - Go: go.mod / go.sum - Rust: Cargo.lock - PHP: composer.lock - Java: pom.xml / build.gradle - .NET: *.csproj / packages.lock.json ## Outputs - **report**: structured JSON objects describing the advisories affecting the audited packages. - **summary**: Markdown summary including total vulnerabilities, severity breakdown, and key findings. ## LLM usage guidelines - Never guess whether a package is vulnerable — always call this tool. - Only submit PURLs from the supported ecosystems listed above; others will be ignored. - The `summary` is already Markdown and can be shown directly. - Use `report` when deeper technical analysis is required.

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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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• optimize_prompt

  pqs-mcp-server

  Rewrite a prompt to score higher on the PQS rubric, AND show before/after output comparisons so the user can see the impact. Returns the optimized prompt, the original PQS score, the optimized PQS score, and side-by-side sample outputs from a frontier model using both versions. USE WHEN: - The user got a low score from score_prompt and asks how to improve. - The user explicitly asks to "improve" / "rewrite" / "fix" / "optimize" a prompt they pasted. - The user is dissatisfied with output quality from a previous prompt and asks how to get better results. - score_prompt returned a suggestion to invoke this tool. DO NOT USE WHEN: - The user just asked for a score (use score_prompt only — don't double up). - The user wants you to write a new prompt from scratch (write it directly). REQUIRES: A PQS API key from a Pro subscription ($19.99/month, 1,000 calls/mo, includes batch + A/B comparison). If the user has not provided one, the tool returns a clear subscription URL — pass that response to the user verbatim. Do not invent or guess API keys. There is no free trial of this tool; the user must subscribe before the first call. COST: Counted against your Pro subscription's monthly call quota. LATENCY: ~6-8 seconds.

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• optimize_prompt

  PQS - Prompt Quality Score

  Rewrite a prompt to score higher on the PQS rubric, AND show before/after output comparisons so the user can see the impact. Returns the optimized prompt, the original PQS score, the optimized PQS score, and side-by-side sample outputs from a frontier model using both versions. USE WHEN: - The user got a low score from score_prompt and asks how to improve. - The user explicitly asks to "improve" / "rewrite" / "fix" / "optimize" a prompt they pasted. - The user is dissatisfied with output quality from a previous prompt and asks how to get better results. - score_prompt returned a suggestion to invoke this tool. DO NOT USE WHEN: - The user just asked for a score (use score_prompt only — don't double up). - The user wants you to write a new prompt from scratch (write it directly). REQUIRES: A PQS API key from a Pro subscription ($19.99/month, 1,000 calls/mo, includes batch + A/B comparison). If the user has not provided one, the tool returns a clear subscription URL — pass that response to the user verbatim. Do not invent or guess API keys. There is no free trial of this tool; the user must subscribe before the first call. COST: Counted against your Pro subscription's monthly call quota. LATENCY: ~6-8 seconds.

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• get_project_info

  Fractera

  Project reference / help desk about Fractera. Use this to answer ANY user question about what Fractera is, how it works, its architecture, components, modes, data ownership, pricing, use cases, partner program, etc. — especially while a deploy is running and the user wants to learn more. TOKEN-ECONOMY: call with NO arguments first to get the lightweight list of section ids+titles, then call again with a single `section` id to fetch just that section. NEVER try to fetch everything at once; pull only the section(s) relevant to the user question. Set `lang:"ru"` for Russian-speaking users.

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• mix_colors

  rnv-color-mcp

  Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default, best for on-screen color); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint, use it for physical-media matching); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb. Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects. Use to combine multiple colors into a single blend; to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference.

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• generate_harmony

  rnv-color-mcp

  Generate a color harmony from a base color. base accepts a hex, CSS name, RNV brand name, or saved-palette reference (e.g. 'Spring line:2'). scheme is one of: complementary, analogous, triadic, split-complementary, tetradic (a.k.a. square), monochromatic, compound. Returns a list of hex colors. Read-only and deterministic: it derives the colors from the base and stores nothing, so it has no side effects and is safe to call repeatedly. Use to expand one base color into a related set; to blend existing colors into a single color use mix_colors, and to persist a set you like use save_palette.

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• create_application

  FlowCastle

  Create a new application (workspace) owned by the caller. Requires a personal API key (usr_...) — application-scoped keys cannot create applications. Seeds default flows unless skipDefaultFlows is true. Creates persistent state and is NOT idempotent: calling it twice creates two applications. Returns the new application id, which you then pass as applicationId to the other tools.

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• submitExperienceApplication

  Nomad Stays

  Submit a completed Experience Application for human review. Rejects with a missingFields list if any required field is still empty, or a 409 if the Application Fee hasn't been paid/waived yet (call purchaseProduct with productId 9 and applicationId first — Experience uses product 9, NOT product 8). There is no partial/optimistic submission. On success the application moves to human review. Requires NOMADSTAYS_MCP_AGENT_TOKEN.

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• appinsights_set_connection

  ALM X++ MCP Server

  Securely register the D365 F&O environment's Application Insights / Log Analytics connection for the CURRENT session. The client secret is encrypted in memory (AES-256-GCM), never written to disk and never echoed back. Once set, appinsights_query and appinsights_diagnose_slowness use it automatically until it expires or you call appinsights_clear_connection. HOW TO GET THE VALUES: workspaceId -- the Log Analytics WORKSPACE ID (GUID, not the App Insights app id) behind the Application Insights resource the environment is linked to (D365FO: System administration > Monitoring and Telemetry parameters > Application Insights Registry tab shows the connection string; the workspace id is on that Log Analytics workspace resource's Overview blade in the Azure Portal). tenantId/clientId/clientSecret -- an Entra ID app registration granted the 'Log Analytics Reader' (or 'Monitoring Reader') role on that workspace resource (Azure Portal > workspace > Access control (IAM) > Add role assignment). Read-only -- no write access is ever needed or used. In a locked server deployment (APPINSIGHTS_LOCK_SERVER_CONFIG=true) this tool is disabled and the server's own environment credentials are used instead.

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• get_sites_by_state

  USGS Water Monitoring

  Find USGS water monitoring sites in a state. Returns a list of monitoring stations with their site numbers, names, and locations. Use site numbers with get_water_levels to retrieve data. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'TX'). site_type: Type of monitoring site. 'ST' for stream/river, 'GW' for groundwater well, 'SP' for spring. limit: Maximum number of sites to return (default 50).

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• get_integration_guide

  TestMyVibes

  Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.

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• get_project_info

  Fractera

  Project reference / help desk about Fractera. Use this to answer ANY user question about what Fractera is, how it works, its architecture, components, modes, data ownership, pricing, use cases, partner program, etc. — especially while a deploy is running and the user wants to learn more. TOKEN-ECONOMY: call with NO arguments first to get the lightweight list of section ids+titles, then call again with a single `section` id to fetch just that section. NEVER try to fetch everything at once; pull only the section(s) relevant to the user question. Set `lang:"ru"` for Russian-speaking users.

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• get_wildfire_perimeters

  KAZM Mellow Mountain Radio

  Returns active wildfire incidents within ~150 miles of Sedona from the National Interagency Fire Center (NIFC). Especially critical during Arizona fire season (April–July). Returns name, acreage, containment, and distance from Sedona.

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• clerk.rotate_oauth_application_secret

  Vee3

  Rotate the client secret for a confidential OAuth application in a connected Clerk application. **Sensitive** — the response includes a new client_secret. Update authorized OAuth clients immediately and do not log the secret. Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account. Returns the updated OAuth application summary with the new client_secret. Cost = 10 tokens.

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• aetherwave_balance

  AetherWave Studio

  Returns the current AetherWave credit balance for the API key. Use this BEFORE a generation to confirm sufficient credits, especially for video which can cost 30-300+ credits depending on model/duration/resolution.

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• explain_three_primitives

  DiscreteRate

  Return a focused write-up of the three DRS modeling primitives: Constraint (rate-limiter), Buffer (accumulated state), Interrupt (stoppage). Use this when the user asks specifically about modeling primitives or how to spell a system in DRS. Deterministic text.

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• score_prompt

  pqs-mcp-server

  Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

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