"Assistance with Java development" matching MCP tools:

• sti_search

  Stimulsoft Documentation MCP Server

  Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.

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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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• get_indicator

  worlduank

  Get World Bank time-series data — economic, social, and development statistics — for ANY country worldwide (Spain, Brazil, Germany, Nigeria, Japan, etc.). PREFER for "unemployment rate in <country>", "<country> inflation rate", "GDP of <country>", "<country> population / life expectancy / poverty rate / CO2 emissions". Pass the ISO country code + a World Bank indicator code; common ones: GDP=NY.GDP.MKTP.CD, GDP per capita=NY.GDP.PCAP.CD, inflation=FP.CPI.TOTL.ZG, unemployment=SL.UEM.TOTL.ZS, population=SP.POP.TOTL, life expectancy=SP.DYN.LE00.IN, poverty rate=SI.POV.DDAY, literacy=SE.ADT.LITR.ZS. For CO2 use the dedicated country_co2_emissions tool (the old EN.ATM.CO2E.* codes were DELETED by the World Bank; the live series is EN.GHG.CO2.MT.CE.AR5). (Annual data — a national statistics office may have fresher monthly figures.)

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• ibge_malhas_tema

  IBGE Brasil MCP

  Gets thematic geographic meshes from IBGE. Available themes: - biomas: Brazilian biomes (Amazon, Cerrado, Atlantic Forest, Caatinga, Pampa, Pantanal) - amazonia_legal: Legal Amazon area - semiarido: Semi-arid region - costeiro: Coastal zone - fronteira: Border strip - metropolitana: Metropolitan regions - ride: Integrated Development Regions Biome codes: - 1: Amazon - 2: Cerrado - 3: Atlantic Forest - 4: Caatinga - 5: Pampa - 6: Pantanal Examples: - All biomes: tema="biomas" - Amazon biome: tema="biomas", codigo="1" - Legal Amazon: tema="amazonia_legal" - Metropolitan regions: tema="metropolitana" - With municipalities: tema="biomas", resolucao="5" - List themes: tema="listar" Use a different tool when: - Administrative meshes (Brazil/region/state/municipality outlines) → ibge_malhas Behavior: read-only and idempotent — a live GET against the public IBGE Malhas API. Returns the mesh in the requested format (GeoJSON, TopoJSON, or SVG).

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• send_message_to_provider

  Clutch.co

  Reach out to a service provider to get a quote, discuss project needs, explore a partnership, find a job, etc. This tool sends the SAME message to one or more providers via `provider_ids` in a SINGLE call - do not call it multiple times. Never invent provider IDs and never ask the user to supply them. Message composition: - If the user provides a ready-made message, send it as-is without modifications. - If the user describes their intent without providing a message, compose one on their behalf based on their requirements and the conversation context. Keep the composed message concise and grounded strictly in the information provided by the user — do not add details that were not mentioned. - The same message and subject are sent to every provider in the call, so do not include any provider-specific information. Examples: - "Message the top 3 about my web development project" -> provider_ids=[<id_1>, <id_2>, <id_3>] (IDs of the top 3 providers shown earlier), compose message based on context, subject="Get a quote / discuss my project needs" - "Request a quote from all of these providers" -> provider_ids=[<all provider IDs shown above>], subject="Get a quote / discuss my project needs" - "Send to WebFX and Acme: I saw your profile and I'm interested in joining your team" -> provider_ids=[<webfx_id>, <acme_id>], message="I saw your profile and I'm interested in joining your team", subject="Find a job" The user must be logged in to Clutch to use this tool.

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• niche_angle_propose

  Niche — Editorial Intelligence

  Niche content angles: pick a story from the discovery slate and surface the strongest angles worth publishing, the editorial-judgment step that turns a development into a piece. Returns five angles[], each with frame, hook, tension, cta_direction, and cta_variants (a swap palette). niche_session_state then carries an angle_recommendation (recommended_angle_id plus reasoning); when a brand profile is bound it is brand-fit-scored, otherwise recommended_angle_id is null with recommendation_basis='default_ordering' (no invented pick). Returns immediately with status=cp2_generating; poll niche_session_state until angles[] is populated. Custom framing (provenance-preserving): to draft your own angle on this researched story, not one of the proposed five, pass `custom_framing` (after the story is locked and angles are ready). The framing is shaped onto the real story and drafted on this session, so the trust block keeps the story's actual sources. Use this instead of niche_draft_direct when you have a researched story in hand; draft_direct works from your take alone, so it has no researched sources to cite. Regenerate: pass `regenerate=true` (story locked, angles ready) for a fresh set of five angles on the same story; pair with `lens` to steer the rerun. Capped per session and metered like a generation.

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• get_sdk_reference

  Senzing

  Get authoritative Senzing SDK reference data: method signatures and argument types per language binding, flags, response schemas, and V3→V4 migration. Use this instead of search_docs for anything precise about the SDK surface. Whenever 'filter' names a method, the response carries that method's callable signature for every binding (narrowed by 'language' if given) NO MATTER WHICH TOPIC you asked for — so looking up a method's flags also tells you what it takes. Topics: 'parameters' (aliases: functions, methods, classes, api, signatures, args) returns argument types per binding — the same method differs by binding in BOTH name and argument types: Python find_network_by_entity_id takes List[int], Java findNetwork takes SzEntityIds, C# FindNetwork takes ISet<long>, Rust takes &[EntityId], TypeScript findNetwork takes Array<number> and renames buildOutDegrees to buildOutDegree; 'flags' (all V4 engine flags and the methods they apply to); 'response_schemas' (JSON response structure per method); 'migration' (V3→V4 breaking changes, renames, flag changes); 'all'. 'filter' accepts any spelling — 'get entity', 'get_entity', and 'getEntity' all resolve. Pass 'language' (python/java/csharp/rust/typescript) to narrow to your binding; cross-binding divergence warnings are still included so you never translate a call between bindings by mistake

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• sti_search

  docs

  Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.

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• plan_deploy

  mcp

  Turns YOUR repo classification (you scan the repo and pass what you found) into a complete, approvable deploy plan WITHOUT creating anything. ⚡ PASTE THREE FILES IF THEY EXIST - `redu_md` (cat redu.md), `compose_yaml` (the compose file), `dockerfile`. You do NOT read or interpret them; redu parses them SERVER-SIDE and returns (a) a short digest, (b) `pin_dname` so a redeploy keeps the SAME public URL, and (c) `preflight` - preemptive fixes for known failure patterns found in YOUR repo, each learned from a real failed build. Pasting them is the single highest-value thing you can do for a first deploy. picks the VM + managed-Postgres sizes, prices them at the real pricing_rules rates, and checks they FIT your quota — so a plan that can't provision is caught HERE, before any spend. You pass what you detected in the repo (runtime, port, needs_postgres/redis/clickhouse/vector_db); it returns resources + £/hr + £/mo + a feasibility verdict + a checkpoint summary to confirm with the user. Defaults: app VM m1.medium, managed Postgres m1.small, managed ClickHouse m1.medium; pass single_vm to collapse the app + Postgres onto one VM. SET needs_clickhouse:true FOR ANY ANALYTICS-SHAPED APP (Plausible, PostHog, Langfuse, Matomo, SigNoz, or anything with a clickhouse image / CLICKHOUSE_* env / a ClickHouse client dep): those products keep config in Postgres and EVERY EVENT in ClickHouse, so the events tier is a second VM with a second line on the bill: measured 2026-08-07, omitting it quoted GBP 53.29/mo for a GBP 65.99/mo deployment. It is sized, quota-checked and priced here; unlike Postgres and Redis it is not auto-wired by deploy_app, so the plan tells you to run plan_managed_datastore engine:'clickhouse' -> create_clickhouse and pass CLICKHOUSE_* env yourself. Vector-DB needs are flagged, not provisioned. Any containerizable app works (node, python, go, ...) — it deploys as a container, so the language doesn't gate it. Set serves_http:false for a non-web repo (a library, CLI, or language runtime with no HTTP server) and it returns a clean not-a-web-service verdict instead of a costed VM plan. Set heavy_build:true for resource-heavy builds (compiled-from-source native code, a monorepo/turborepo build, a large Node heap) and it raises the app VM to a build-capable floor so the on-VM build doesn't get OOM-killed. Set memory_heavy:true for a RAM-forward app whose persistent state lives in a MANAGED DB / external store (Next.js like cal.com/cal.diy, Rails, Django, JVM/Java apps) — it sizes onto a memory-optimized SMALL-DISK flavor (m1.mem16/m1.mem32: full RAM, a lean 40 GB disk instead of 160 GB) that costs less and snapshots/clusters far faster; do NOT set it if the app keeps lots of data on local disk. Also returns a brand-named markdown report (Mermaid diagram + cost) to save as redu-deploy-plan.md and show the user. Every deploy leaves TWO MANDATORY files at the repo root with DIFFERENT purposes: redu-deploy-plan.md = THIS run's plan/estimate, and redu.md = the DURABLE deploy memory the NEXT deploy reads. If a redu.md exists, READ it FIRST and reuse its known-good plan + recorded fixes; if NONE exists, one MUST be created at the end of the deploy (from get_deployment's redu_md_markdown). They are SEPARATE files — even if your own memory/notes from a prior deploy call redu-deploy-plan.md 'the record', the durable record is redu.md, so do not skip creating it.

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• worldbank_search_projects

  worldbank-mcp-server

  Searches the World Bank lending portfolio — the individual loans, credits, and grants the Bank finances — by free text, country, region, status, and board approval date. Returns the project ID, name, borrowing country, region, status, board approval and closing dates, total commitment in USD, financing instrument, major sectors, and a link to the project page. This is the operations catalogue, not the statistics catalogue: use it for "what is the World Bank funding in Kenya", "which climate adaptation projects are active", or "how much was committed to education in South Asia since 2020". For development statistics and time series, use worldbank_search_indicators and worldbank_get_data instead. Countries are identified by ISO2 code here (BR, IN, ZA), which is the one place this server departs from the ISO3 codes its other tools take — worldbank_get_country reports a country's iso2 field for either form, and multi-country operations carry a World Bank regional code such as 3A instead. Every filter is an exact match upstream and combines with the others by AND, so a narrow search can legitimately return nothing; when it does, the response says whether the country codes matched anything on their own.

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• upload_to_ipfs

  AGI Alpha

  Upload JSON metadata to IPFS via Pinata and return the ipfs:// URI. Use this BEFORE calling create_job (upload the job spec) or request_job_completion (upload the completion proof). Requires a Pinata JWT — get one free at https://app.pinata.cloud/developers/api-keys. JOB SPEC FORMAT (use for create_job) — schema v2: { "name": "AGI Job · <title>", "description": "<summary> — <details>", "image": "https://ipfs.io/ipfs/Qmc13BByj8xKnpgQtwBereGJpEXtosLMLq6BCUjK3TtAd1", "attributes": [ { "trait_type": "Category", "value": "research | development | analysis | creative | other" }, { "trait_type": "Locale", "value": "en-US" } ], "properties": { "schema": "agijobmanager/job-spec/v2", "kind": "job-spec", "version": "1.0.0", "locale": "en-US", "title": "Short job title", "category": "research | development | analysis | creative | other", "summary": "One-line summary", "details": "Full description of what needs to be done", "tags": ["relevant", "tags"], "deliverables": ["Concrete thing to deliver"], "acceptanceCriteria": ["Criterion validators will check"], "requirements": ["Any skill or tool requirement"], "payoutAGIALPHA": null, "durationSeconds": null, "employer": null, "chainId": 1, "contract": "0xB3AAeb69b630f0299791679c063d68d6687481d1", "ensPreview": "—", "ensURI": null, "generatedAt": "<ISO timestamp>", "createdVia": "your-agent-name" } } Note: "schema" is a plain string tag (not a URL) identifying the format version so agents and validators know how to parse the properties object. COMPLETION FORMAT (use for request_job_completion): { "name": "AGI Job Completion · <job title>", "description": "Final completion package for Job <jobId>. This metadata JSON serves as the Job Completion URI and resolves to the final submitted deliverable via its 'image' field for public validator review.", "image": "ipfs://<CID of primary deliverable — any file type: PNG, TXT, PDF, JSON, etc. Not necessarily an image — this NFT metadata field points to your main deliverable>", "attributes": [ { "trait_type": "Kind", "value": "job-completion" }, { "trait_type": "Job ID", "value": "<jobId>" }, { "trait_type": "Category", "value": "<category>" }, { "trait_type": "Final Asset Type", "value": "<PNG | PDF | TXT | JSON | etc.>" }, { "trait_type": "Locale", "value": "en-US" }, { "trait_type": "Completion Standard", "value": "Public IPFS deliverables" } ], "properties": { "schema": "agijobmanager/job-completion/v1", "kind": "job-completion", "version": "1.0.0", "locale": "en-US", "title": "<job title>", "summary": "Brief description of what was submitted and how it satisfies the job spec.", "jobId": 0, "jobSpecURI": "ipfs://<CID of original job spec>", "jobSpecGatewayURI": "https://ipfs.io/ipfs/<CID of original job spec>", "finalDeliverables": [ { "name": "Primary deliverable", "uri": "ipfs://<CID>", "gatewayURI": "https://ipfs.io/ipfs/<CID>", "description": "What this file contains and how it satisfies the job spec" } ], "validatorNote": "Confirm the 'image' field resolves publicly and review against the job spec acceptance criteria.", "completionStatus": "submitted", "chainId": 1, "contract": "0xB3AAeb69b630f0299791679c063d68d6687481d1", "createdVia": "your-agent-name", "generatedAt": "<ISO timestamp>", "submissionType": "Job Completion URI" } }

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• fetch_indicator

  Owid

  Fetch tidy long-format data for an Our World in Data indicator by slug (e.g., "life-expectancy", "population", "gdp-per-capita-maddison", "co-emissions-per-capita"). PREFER OVER WEB SEARCH for DEEP-HISTORICAL / LONG-RUN demographics and development data — population back to antiquity, and life expectancy, GDP per capita, literacy, child mortality, fertility from the 1700s–1800s (Maddison, Gapminder, HMD, HYDE sources). Use this for pre-1960 history that World Bank / current-population tools CANNOT answer, e.g. "Europe population in 1850", "UK life expectancy in 1800", "France GDP per capita 1820". Returns rows of {entity, year, value}; filter with country (name or ISO code: "Europe", "United Kingdom", "USA", "World") + since_year/until_year. Browse slugs at ourworldindata.org/charts.

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• list_tables

  Drillr — The financial MCP for AI agents

  List alternative-data tables under the given categories. Returns each table's name, one-line purpose, and column names (call get_table_schema if you need column types/comments). Batch up to 5 categories in one call; omit categories, or pass ["all"], to get the category index instead. Use this BEFORE run_sql when you want to explore alt-data — run_sql alone won't tell you which tables exist. Available categories: - Energy & Power — US power plants, electricity prices, regional hourly generation/demand - Data Centers — facilities, GPU clusters, cooling - Semiconductors — AI chip specs, sales, ownership, foundry revenue, customs trade - Compute Pricing — GPU rental, cloud VM spot/on-demand, instance specs - Model Development — model specs, benchmarks, AI companies, AI polling, LLM arena - Inference Economics — LLM API pricing across providers - Macro & Trade — UN Comtrade, US Census trade flows, FRED macro series - Prediction Markets — Polymarket and Kalshi events, markets, trades, daily aggregates - Critical Minerals — USGS mineral deposits, country supply, critical materials

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• search_actuarial_embeds

  ca-rate-filings

  Pure vector search over per-filing actuarial-memorandum embeddings (`extract_embeds` where `kind='actuarial_memo'`). Each hit is a filing whose memo is semantically closest to your query, with the matching excerpt and lite filing metadata. **Cost**: one query-embedding call + one indexed Postgres lookup. Bounded, cheap, fast. No LLM planning, no LLM composition. **This is the right tool any time the question is *actuarial-shape*.** Reach for it — not `search_summary_embeds` and not `search_filing_embeds` — when the user is asking about: - Rate adequacy: headline rate change, indicated vs selected, off-balance, capping. - Loss trends: severity trend, frequency trend, pure-premium trend, projected ultimates, LDFs, IBNR development. - Credibility / experience: experience period, weight assigned to own experience vs class-plan / bureau, credibility tables. - Expense / profit provisions: permissible loss ratio, target combined ratio, profit & contingency loading, expense ratio, investment-income offset. - Reason codes / drivers: reinsurance cost, weather/cat load, severity-driven rate need, mix shift, frequency reductions from telematics. - Anything where the answer would be a *number from the actuarial memo* rather than a description of what the filing does. The memo is where actuaries put the numerics; the extraction summary is where the pipeline puts the prose. If the question reaches for numbers, hit this surface first. **Wrong surface for**: - *Content* questions ("filings discussing wildfire scoring", "telematics programmes", "parametric triggers") — those discuss what the filing is *about*, not actuarial numerics. Use `search_summary_embeds` (broader coverage). - Concrete-filter questions ("Filings from carrier NAIC 12345 in 2024") — use `search_filings`. - Filings with no actuarial memo. Memos are typically attached to Rate filings; Form, Rule, and Withdrawal filings often have none. Coverage is narrower than `search_summary_embeds` for that reason — most of the 2026 corpus is covered, prior years are backfilling. **How to combine**: - "Personal auto filings in California whose indicated rate exceeds selected by 5+ points" → `search_filings` (state=CA, product_type="Personal Auto", filing_type="Rate") to scope a candidate set, then this tool over the candidates' memos. - "Carriers citing severity-driven rate need in 2025" → this tool first; `get_filing_summary` on the top hits to read in full. Returns top-K hits, each with `{serff, similarity, excerpt, meta}`. Default `topK=10`, max 50. Excerpt is the first 800 chars of the matching memo.

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• check_injection

  ContrastAPI

  Scan source code for injection vulnerabilities: SQL injection, command injection, path traversal via unsafe string concatenation/unsanitized input. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect input-handling bugs; for secrets use check_secrets. Companion code-security tools: check_secrets (hard-coded credential detection), check_dependencies (known-CVE vulnerability audit), check_headers (live HTTP security-header validation), scan_headers (live HTTP scan via domain). Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored.

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• query_context

  mcp-klever-vm

  Search the Klever VM knowledge base for smart contract development context. Returns structured JSON with matching entries, scores, and pagination. Use this for precise filtering by type or tags; use search_documentation for human-readable "how do I..." answers.

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• paywall__customer_deduct_from_fup

  Netfluid

  Deducts a unit from the customer's available workflow allowance. Do not call this tool when the customer is requesting assistance related to the pay wall and its subscriptions. This tool should be called after each AI response that is not pay wall related. @param customer_id: The customer's database id @return: a json object, containing the customer_id and remaining fup token balance in the "values" object

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• search_jobs

  Dice MCP

  Search for job listings by keyword, location, and filters. Returns job details, company info, and application links. Use this tool when users want to find jobs, search employment opportunities, or explore job openings. DO NOT use for: applying to jobs, submitting applications, or making employment decisions. LLM USAGE INSTRUCTIONS: - ALWAYS provide the keyword parameter (required) - When presenting results to users, include BOTH the job details URL (detailsPageUrl) AND the company page URL (companyPageUrl) for each job - Use location to find geographically relevant positions - Combine filters to refine searches (e.g., workplace_types=['Remote'] for remote work) - Use posted_date to find recent openings ('ONE'=1 day, 'THREE'=3 days, 'SEVEN'=7 days) - Default jobs_per_page is reasonable, increase for comprehensive searches - Use company_name to scope results to a specific employer - Use sort='datePosted' when the user wants the newest listings instead of the most relevant - Use facets to get aggregate counts (e.g., how many results are remote vs on-site) without paging through all results - After presenting results, do NOT automatically call get_job_details for every job returned. Wait for the user to indicate which specific job(s) they're interested in, then pass that job's guid to get_job_details. IMPORTANT - AI DISCLOSURE REQUIREMENT: When presenting job search results to users, you MUST include an appropriate disclosure that these results were retrieved using AI assistance. Example disclosure language: "These job listings were found using AI-powered search. Please review all job details carefully and verify information directly with employers before applying." This tool provides job listing data only. Final employment decisions should always involve human judgment and direct review of complete job postings. Args: keyword: The job keyword or title to search for (required) location: Geographic location for the job search (city, state, country) radius: Search radius from the specified location (minimum 1, requires radius_unit) radius_unit: Unit for search radius. Options: 'mi', 'km' (requires radius) jobs_per_page: Number of jobs to return per page (1-100, defaults to 5) page_number: Page number for pagination (1-based, default is 1) sort: Sort order for results. Options: 'relevance', 'datePosted' (defaults to relevance) posted_date: Filter by posting date. Options: 'ONE' (1 day), 'THREE' (3 days), 'SEVEN' (7 days) workplace_types: Workplace arrangements. Options: 'Remote', 'On-Site', 'Hybrid' employment_types: Employment types. Options: 'FULLTIME', 'CONTRACTS', 'PARTTIME', 'THIRD_PARTY', 'INTERNSHIP' employer_types: Employer types. Options: 'Direct Hire', 'Recruiter', 'Other' willing_to_sponsor: Filter for employers willing to sponsor work authorization (boolean) easy_apply: Filter for jobs with easy application process (boolean) company_name: Filter by company name fields: Specific fields to include in response (optional, returns all exposed fields by default) facets: Facet dimensions to aggregate (optional). Options: 'employmentType', 'postedDate', 'workFromHomeAvailability', 'workplaceTypes', 'employerType', 'easyApply', 'isRemote', 'willingToSponsor' Returns: JobSearchResult: Contains: - data: List of JobDisplayFields with job details including: * guid: The job's identifier to pass as job_id to get_job_details for the full description and skills list (NOT the `id` field, which is a different, internal identifier not accepted by get_job_details) * detailsPageUrl: Direct link to full job posting * companyPageUrl: Link to company profile page * title, summary, salary, location, employmentType, etc. - metadata: Search metadata with pagination info and facet results Raises: Exception: If API call fails or input validation errors occur

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• lts_by_city

  LTS MCP Server

  Rank cities by LTS count with province, region, law breakdown, active/expired split, and top developer per city. Groups by city+province to avoid merging same-name cities across provinces. Use for housing pressure indices, city-level market analysis, and identifying emerging development hotspots. Cross-reference with PSGC MCP for city classification and population. Capped at 25k rows; check truncated flag and narrow filters if true.

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