"AI-powered IDEs for project analysis and development" matching MCP tools:

• analyze_company

  Nordic Financial MCP

  AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'

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• ir_get_brief_template

  website-search

  Get Lenny Zeltser's IR one-page executive brief template. Standalone variant of `ir_get_template` for callers that only want the brief without the long-form report. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.

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• cti_get_brief_template

  website-search

  Get Lenny Zeltser's CTI one-page executive brief template. Standalone variant of `cti_get_template` for callers that only want the brief without the long-form report. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.

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• generate_framework_analysis

  jeda-ai

  Runs a specific framework against a user's inputs and produces a full analysis: prose explanation + structured fields + a self-contained SVG visualisation. Powered by the Jeda.ai · Visual AI framework knowledge graph. ALWAYS call `recommend_framework` FIRST to obtain a valid framework_id -- it returns the exact namespaced slug to pass here. Framework ids are namespaced by category (e.g. SWOT = "cms_swot-analysis", Porter's 5 Forces = "cms_porters-five-forces"); a bare slug like "swot-analysis" will 404. REQUIRED post-processing on success: the response's first text block contains a `curl -fsSL` save-directive for the SVG. Save the file locally and surface it as a file chip — do NOT summarise the visual in prose. Input: framework_id (namespaced slug from `recommend_framework`) + user_inputs object (per-framework field set), OR a free-text `raw_prompt` fallback. Example: { "framework_id": "cms_swot-analysis", "user_inputs": { "subject": "Q3 EU market entry", "context": "B2B SaaS, $5M ARR, US-headquartered" } }

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• malware_get_template

  website-search

  Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

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• malware_get_cross_server_routes

  website-search

  Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

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• malware_get_frameworks

  website-search

  Get Lenny Zeltser's Malware frameworks (primary frameworks the brief structurally derives from) plus optional sibling frames (adjacent frameworks that aren't the structural backbone). Pass `include_siblings: false` to skip sibling blocks. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

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• assessment_get_brief_template

  website-search

  Get Lenny Zeltser's Security Assessment one-page executive brief template. Standalone variant of `assessment_get_template` for callers that only want the brief without the long-form report. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.

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• __unlock_blockchain_analysis__

  mcp-server

  Mandatory initialization step for any session against the Blockscout MCP server. Returns server reference data plus the `blockscout-analysis` skill pointer and URI resolution rule. MANDATORY FOR AI AGENTS: Call this tool first in every session. The returned payload identifies where the operating rules and analysis framework live and how to read referenced skill files before executing further tool calls.

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• __unlock_blockchain_analysis__

  blockscout-mcp-server

  Mandatory initialization step for any session against the Blockscout MCP server. Returns server reference data plus the `blockscout-analysis` skill pointer and URI resolution rule. MANDATORY FOR AI AGENTS: Call this tool first in every session. The returned payload identifies where the operating rules and analysis framework live and how to read referenced skill files before executing further tool calls.

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• aidefense_evaluate_program

  website-search

  Get the AI Defense Matrix evaluation playbook for assessing an AI security program: per-cell prompts, gap-inventory template, and a workflow that walks each asset class first and rolls findings up to the Govern column. Supports mode='gate' for binary deployment-gate decisions (returns the deployment-gate workflow plus gate-tier prompts only) and consumerPattern for scoping to consumed-vs-built AI deployments. The AI applies these prompts against your program documentation locally, and no program details leave your client. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.

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• aidefense_cross_map

  website-search

  Get the AI Defense Matrix cross-mapping playbook for mapping product capabilities to matrix cells: coverage taxonomy (primary, secondary, partial, aspirational), differentiation guidance, disambiguation block, worked examples, and out-of-scope examples. The response always includes an inScopeCheck. Products that USE AI to solve a non-AI security problem (deepfake detection, AI-for-fraud, AI features added to existing SIEM, SOAR, or EDR tools) belong in the Cyber Defense Matrix at https://cyberdefensematrix.com. Pairs naturally with product_load_context(productFocus: 'ai_security') for follow-on positioning and GTM work. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.

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• get-code-vault-results

  coderegistry

  Returns analysis results for a vault. Free-tier teams receive summary-only results; paid teams receive full facet data and AI insights. Analysis is async; if status is 'processing', poll with exponential backoff (5s, 10s, 20s, 40s, max 60s). Analysis can be as quick as 20-30 minutes for under 500,000 lines of code. Larger codebases can take much longer, especially with the security scan. Facet meanings are documented in resources://docs/facets; AI Quotient is a code-quality metric (not AI-generated code). AI insights can take a few minutes after analysis completes; if ai_insights is empty, poll again and check ai_insights_status per facet (ready/processing/not_available). This endpoint always returns the latest version only; once reanalysis starts, prior versions are no longer accessible here. Requires X-API-Key (existing users can generate an API key in the web app). If headers aren't supported, pass api_key in arguments.

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• tascan_list_issues

  TaScan

  List all issues for a task list (event). Returns open, acknowledged, and resolved issues with severity, type, and category. Use this to discover issues that need AI analysis via tascan_analyze_issue.

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• tourradar_vertex-tour-title-search

  MolTravel

  [tourradar] Search for tours by title using AI-powered semantic search. Returns a list of matching tour IDs and titles. Use this when you need to look up a tour by name. When you know tour id, use b2b-tour-details tool to display details about specific tour

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• donate

  Blueprint Agentic Staking (Solentic)

  Build an unsigned SOL transfer to support Blueprint development. Blueprint provides free staking infrastructure for AI agents — donations help sustain enterprise hardware and development. Same zero-custody pattern: unsigned transaction returned, you sign client-side. Suggested amounts: 0.01 SOL (thank you), 0.1 SOL (generous), 1 SOL (patron).

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• feature_request

  Caliper

  Request a feature or format that Caliper doesn't support yet. Free, no payment required. Use this when you need a capability that Caliper doesn't currently offer — especially unsupported file formats (STEP, IGES) or analysis features not yet available. Requests are logged and used to prioritize development. Privacy policy: https://caliper.fit/privacy

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• development_appraisal

  property-finance-mcp

  Run a UK property development scheme viability appraisal. Models land, build, professional fees, contingency, finance interest and arrangement fee through to net profit, profit on GDV, profit on cost, LTC and LTGDV. Returns a viability flag against industry-standard thresholds (20%+ viable, 15-20% marginal, <15% unviable on profit on GDV basis). Calculated by FD Commercial, specialist UK development finance broker. Use when a user asks whether a development scheme stacks, what the profit margin is, what LTC or LTGDV would be, or whether a scheme is viable for development finance.

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• cti_load_context

  website-search

  Load Lenny Zeltser's CTI writing context for local analysis. Returns a JSON payload with section guidance, completeness criteria, framework grounding (12 frameworks), the six attribution signals, ICD-203 confidence levels and ladder, and the Pyramid of Pain. The 'profile' parameter ANNOTATES sections (internal/public applicability label) rather than filtering — every section is returned so cross-profile comparisons are possible. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.

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• vertical_ai_agent_governance

  gapup-mcp

  Generates a comprehensive vertical AI agent workforce integration plan for CHROs, including governance frameworks, human-AI collaboration metrics, and upskilling recommendations. Inputs: industry vertical, workforce size, and current AI adoption level. Outputs: role-specific AI integration roadmaps, skill gap analysis, and performance benchmarks. Uses O*NET skill taxonomies and Gartner AI adoption trends. For best results with large datasets, pass async:true to avoid timeout.

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