MCP Server – File Search Tool

The File Search Tool is an MCP server that exposes a rich set of file‑system operations over the Model Context Protocol. It lets an AI assistant query, list, and read files from a pre‑approved set of directories while maintaining strict security controls. By providing structured file metadata and content through MCP, the server removes the need for custom integrations or manual file handling in AI workflows.

Why It Matters

Developers building knowledge‑base assistants often need to surface relevant documents, code snippets, or configuration files. Traditional approaches involve embedding file‑system access into the assistant’s prompt logic or writing bespoke adapters. This MCP server abstracts those details, offering a single, declarative interface that can be queried by any AI client. It also ensures compliance with data‑access policies: administrators specify allowed and excluded paths, hide hidden files, and even mask sensitive portions of file paths before they reach the assistant.

Core Capabilities

• Directory Listing – Retrieve a breadth‑first or depth‑first enumeration of files and subdirectories, with paging support to handle large trees.
• File‑Name Search – Execute regex searches against file names, returning matching paths along with basic metadata.
• Content Reading – Open plain text, PDF, or DOCX files and return the contents up to an optional character limit.
• Content Search – Perform regex searches within file bodies, delivering the matching lines and configurable context around each hit.
• Path Controls – Enforce allowed directories, block excluded paths, and optionally suppress hidden files.
• Path Masking – Replace specified path segments with a token (e.g., ) to protect sensitive directory structures while still providing useful relative locations.

Real‑World Use Cases

• Documentation Retrieval – An AI assistant can pull the latest README, policy documents, or technical specifications from a controlled repository to answer user queries.
• Code Review Support – Developers can ask the assistant to locate, read, and summarize code files or configuration snippets across a monorepo.
• Compliance Auditing – The server can be configured to expose only audit‑ready directories, enabling the assistant to generate compliance reports without risking accidental data exposure.
• Dynamic Knowledge Base – By indexing a directory of markdown or PDF notes, the assistant can fetch relevant passages on demand, creating an interactive learning aid.

Integration Flow

1. Add the server to the AI client (e.g., Claude Desktop) via a simple command or configuration file.
2. Configure the allowed paths and masking rules in .
3. The AI client sends MCP requests such as or , receiving structured JSON responses.
4. The assistant can then parse the results, embed them in its replies, or pass them to downstream tools (e.g., a summarization model).

Standout Advantages

• Security‑First Design – Explicit path whitelisting and masking keep sensitive data out of the assistant’s view.
• Multi‑Format Support – Built‑in PDF and DOCX readers eliminate the need for external parsers.
• Flexible Search – Regex‑based file and content searches give developers fine control over matching logic.
• Developer Friendly – The server exposes a clean MCP schema, making it straightforward to extend or integrate with other tooling.

In short, the MCP Server – File Search Tool turns a conventional file system into a safe, queryable knowledge source for AI assistants, streamlining development and ensuring that data access remains governed by clear, auditable rules.