"Reading Microsoft OneDrive files" matching MCP servers:

Serves token-efficient code context for AI coding assistants by exposing Python signatures, call graphs, and budget-packed task context as MCP tools, enabling precise codebase queries without reading entire files.

Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.

A deterministic structural code map server for AI agents, giving them the shape of a codebase (imports, exports, classes, functions, signatures, comments, TODO-markers) without reading whole files into context. Powered by tree-sitter WASM grammars, it runs anywhere Node 18+ works.

MCP server that indexes your codebase's public API at startup and serves it via compact tool responses, saving tokens vs reading source files.

An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.

Token-efficient skim-then-expand I/O for agentic models, enabling lossless reading of large files via skeletons and exact expansion with anchor IDs.

A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.

Standard coding agents waste 70% of context tokens re-reading raw files with shell grep. Synapse-MCP indexes your codebase into a sub-millisecond local AST graph—giving Claude Code, Cursor, and Windsurf exact caller trees, 60% lower token spend, and zero-hallucination refactoring.

Enables AI assistants to directly invoke higpertext-cli capabilities as validated MCP tools, covering grep search, git diff and ls-files, smart reading, code skeletonization, knowledge lookup, memory management, committing, secret scanning, and quality resolution without routing through Bash.

MCP server for elaborated SystemVerilog and gate-level netlists. Agents query design structure against a real elaboration - what drives this net, what a module instantiates, what registers are in a fanin cone - instead of reading RTL files. Answers come from najaeda's netlist engine, so they reflect post-elaboration connectivity across hierarchy, not text matches.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Enables efficient code navigation and retrieval through natural language search, BM25 ranking, and fuzzy matching across multiple programming languages. It drastically reduces token usage by allowing Claude to query specific code symbols and logic instead of reading entire files.

Slimdex is a local MCP server that helps coding agents retrieve code narrowly—outlines, line ranges, symbol bodies, references, and intent-based searches—instead of reading whole files into context, featuring a persistent index and tools for exploration, editing, and session memory.

Local MCP server and CLI for Access layout files, rendered to SVG without Microsoft Access. Enables visual verification of form/report layout changes.

A read-only MCP server that gives AI coding agents structured access to a project's source code, architecture, documentation, and Git context through 16 tools for searching, reading, and comparing evidence without modifying files.

Enables AI clients to securely inspect local source repositories with read-only tools for listing files, reading files, and searching text, while enforcing path traversal protection and sensitive-file filtering.

Enables MCP-compatible clients to read repositories and source code from Bitbucket. Provides tools for listing workspaces and repositories, browsing directories, reading files, searching code, and inspecting commits and pull requests.

Gives coding agents structured code understanding via tree-sitter with 23 tools and 10 languages, enabling precise queries instead of reading entire files.

Provides Claude Code with a repository symbol graph via tree-sitter, enabling instant symbol lookup, file skeletons, call-site analysis, and persistent notes, reducing token usage by reading signatures instead of whole files.