Cloud-Dog Secure Search Agent

Executive Overview

Cloud-Dog Secure Search Agent is an enterprise-grade web search and retrieval service that provides controlled, governed access to external internet content for AI agents, workflows and human users. Powered by a configurable searchXNG metasearch engine, it aggregates results from multiple search providers while allowing organisations to define exactly which engines are trusted, permitted and prioritised. Through a standards-compliant MCP interface, the service exposes web search and crawling capabilities as structured tools that can be safely invoked by RAG systems, orchestration layers and AI agents — with proxy, TOR and cookie controls, Infrastructure-as-Code deployment and structured model-ready output. All results are normalised into clean markdown or structured JSON suitable for LLM ingestion, ensuring external intelligence integrates into corporate AI workflows without compromising governance, anonymity or reproducibility.

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Summary

Cloud-Dog Secure Search Agent provides a governed, privacy-controlled MCP interface to configurable web search and retrieval powered by searchXNG. It enables trusted external intelligence gathering for AI agents and workflows, with proxy, TOR and cookie controls, Infrastructure-as-Code deployment and structured model-ready output for secure enterprise environments.

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Features and Benefits

Feature	Benefit
searchXNG-powered configurable metasearch core	Enables safe controlled external web intelligence gathering
MCP-compliant agent interface to web search	Reduces risk of unmanaged AI web browsing activity
Structured markdown and JSON retrieval outputs	Protects organisational anonymity and metadata exposure
Configurable trusted search engine selection	Supports compliant OSINT and research workflows safely
Cookie and tracking minimisation controls	Provides auditable web retrieval operations and evidence
Proxy and TOR routing support for anonymity	Prevents vendor lock-in to single search provider
Distributed deployment for ownership masking	Improves trust in AI-generated web-sourced insights
Async crawl and deep-site retrieval tools	Enhances control over search source integrity
Docker and Infrastructure-as-Code deployment	Supports secure deployment in restricted networks
Governed integration with agent ecosystems	Enables scalable agent-driven web discovery at enterprise scale

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Product Overview

Modern AI systems increasingly require up-to-date external information to deliver accurate, relevant and timely outputs. However, direct browsing by language models or ungoverned HTTP calls introduce significant risk: uncontrolled cookie tracking, IP exposure, data leakage, compliance ambiguity and inconsistent source quality. The Secure Search Agent resolves these issues by acting as a controlled boundary between enterprise systems and the public web — a critical capability for organisations running secure, corporate MCP services in audited environments.

Through a standards-compliant MCP interface, the service exposes web search and crawling capabilities as structured tools that can be safely invoked by RAG systems, orchestration layers, the Cloud-Dog Chat Client and AI agents. All results are normalised into clean markdown or structured JSON formats suitable for LLM ingestion. This ensures that external intelligence can be integrated into AI workflows without compromising governance or reproducibility.

searchXNG is highly configurable. Organisations can specify which upstream search engines are used, including general search, academic search, domain-specific sources or internal federated endpoints. Engines can be prioritised, excluded or weighted according to trust policies. This avoids reliance on a single commercial provider and enables diversification of information sources — reducing vendor lock-in and improving the breadth and reliability of retrieved intelligence.

The platform provides strict control over cookies and tracking artefacts. By minimising persistent identifiers and enabling optional proxy or TOR routing, the Secure Search Agent reduces metadata exposure and supports sensitive investigative, regulatory and OSINT environments where anonymity and operational security are essential.

For organisations operating in restricted or classified networks, the service can be deployed entirely on-premise with controlled egress points, custom certificate authority injection and configurable network boundaries. This ensures that even external web retrieval operates within the organisation's security perimeter and governance framework.

Deployment is container-first and Infrastructure-as-Code friendly, allowing repeatable provisioning across development, test and production environments. The same search configuration that is validated in test can be promoted to production with confidence, ensuring consistent behaviour and policy enforcement across the deployment lifecycle.

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Architecture

The architecture is built around a searchXNG core engine, wrapped by a secure MCP interface layer that enforces governance, authentication and policy controls on every operation.

MCP Interface Layer — Incoming requests are validated, authorised and routed through configured search providers according to enterprise policy. Transport options include stdio, streamable HTTP and JSON-RPC, ensuring compatibility with diverse corporate infrastructure including the Cloud-Dog Chat Client, RAG Agent and Data Agent.

Search Engine Management — The service supports configurable upstream engine lists, weighted engine prioritisation, domain allow-lists and engine rotation policies. Organisations define exactly which search providers are trusted and how results are ranked, aggregated and filtered — maintaining full control over information sources.

Crawl and Retrieval Engine — Crawl operations are bounded by configurable depth and page limits, preventing runaway resource consumption. Async job handling enables long-running site crawls without blocking orchestration flows, with status polling for progress tracking and timeout management.

Network and Privacy Controls — Include proxy configuration, custom certificate authority injection, TOR routing and cookie minimisation. These controls reduce metadata exposure, support anonymity requirements and enable deployment in environments with strict network governance — including restricted, air-gapped and sovereign networks.

Output Normalisation — All retrieved content is normalised into clean markdown or structured JSON suitable for direct LLM consumption. This ensures that downstream agents and workflows receive consistent, well-formatted content regardless of the source website's structure or complexity.

Deployment Infrastructure — Docker-based deployment ensures portability and reproducibility, while Infrastructure-as-Code enables automated provisioning and consistent promotion between environments. Distributed search nodes can be deployed across multiple locations for ownership masking and operational resilience.

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Key Capabilities

Governed Web Search via MCP — Expose configurable multi-engine web search as a structured MCP tool. AI agents, RAG pipelines and orchestration workflows invoke search through a controlled, auditable interface rather than making ungoverned HTTP calls. Language, result count, domain filtering and engine selection are all configurable per request.

Configurable Metasearch Engine Management — Define which upstream search engines are permitted, prioritised and weighted. Combine general search, academic search, domain-specific sources and internal federated endpoints. Implement engine rotation policies and restrict searches to approved domains — maintaining full organisational control over information sources.

Structured Content Retrieval and Normalisation — Retrieve and normalise individual URLs into clean markdown or structured JSON for model consumption. Content is extracted, cleaned and formatted for direct LLM ingestion, removing advertising, navigation and irrelevant elements while preserving substantive content.

Bounded Site Crawling — Perform breadth-first crawling of domains with configurable depth and page limits. Async job handling prevents blocking during long-running crawls, with status polling for progress tracking. This enables systematic intelligence gathering across target domains within controlled resource boundaries.

Privacy and Anonymity Controls — Minimise cookie tracking and persistent identifiers. Enable proxy routing, TOR integration and distributed deployment for ownership masking. These controls support sensitive investigative, regulatory and OSINT environments where anonymity and operational security are requirements, not options.

Restricted Network Deployment — Deploy entirely on-premise with controlled egress, custom CA injection and configurable network boundaries. Operate in private cloud, sovereign cloud, hybrid or air-gapped environments while maintaining governed access to approved external sources through defined channels.

Infrastructure-as-Code Provisioning — Scripted provisioning using standard DevOps tools ensures reproducibility and version-controlled configuration across environments. The same validated search configuration promotes cleanly from development through test to production.

Agent Ecosystem Integration — Integrates naturally with the Cloud-Dog Chat Client for interactive search workflows, the RAG Agent for external knowledge enrichment, and multi-agent orchestration for comprehensive intelligence gathering across internal and external sources.

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Use Cases

1. Governed Web Intelligence — Enable AI agents to search the web safely through controlled, auditable MCP interfaces with policy-defined engine selection.
2. OSINT and Research Workflows — Conduct open-source intelligence gathering with anonymity controls, proxy routing and structured output for analysis.
3. RAG External Enrichment — Augment retrieval-augmented generation workflows with current web content from trusted, configured search sources.
4. Compliance Research — Search regulatory, legal and industry sources with full audit trails and source traceability for compliance reporting.
5. Competitive Intelligence — Monitor competitor websites and industry developments through scheduled crawls with structured change reporting.
6. Restricted Network Search — Operate governed web search from within air-gapped, sovereign or restricted network environments with controlled egress.
7. Multi-Agent Web Discovery — Provide the web search capability for multi-agent workflows coordinated through the Cloud-Dog Chat Client and RAG Agent.