Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Descripción del creador (original en inglés)
Token-efficient MCP server for codebase search, NuGet decompilation, and deep PDF reading.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"dotnetsearch": {
"command": "dnx",
"args": [
"PuneethDC.DotNetSearch",
"--yes"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add dotnetsearch -- dnx PuneethDC.DotNetSearch --yesPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"dotnetsearch": {
"command": "dnx",
"args": [
"PuneethDC.DotNetSearch",
"--yes"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"dotnetsearch": {
"type": "stdio",
"command": "dnx",
"args": [
"PuneethDC.DotNetSearch",
"--yes"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub puneethdc99, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.0.3) llegó al registro hace 11 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas .NET en tu computadora.
En la misma categoría: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
MCP Server Identifier:
mcp-name: io.github.puneethdc99/dotnetsearch
*(Proof of package ownership for GitHub MCP Registry inclusion)*
DotNetSearch is a self-contained MCP (Model Context Protocol) server that empowers GitHub Copilot, Claude, Cursor, and other AI agents with high-performance codebase search, NuGet package decompilation, whitespace token reduction, and deep PDF document reading and analysis:
| Category | Tool | Purpose |
|---|---|---|
| Code Search | search | Find files and lines matching a keyword or natural-language query — returns only matching lines (~110 tokens vs ~2500 for a full file read) |
| Code Search | search_related | Find code chunks structurally similar to a known location — ideal for discovering callers, implementations, or patterns |
| Decompilation | decompile_type | Decompile any .NET type from referenced NuGet package assemblies — returns the full C# class definition without needing the source code |
| Optimization | compress_code | Reduce C# code indentation from 4-space to 1-space per indent level and remove blank lines — saves 10–20% tokens with zero semantic change |
| File Reading | read_file | Read a file from disk and optionally return a specific line range — useful after search when you need full file context |
| PDF Reading | read_pdf_text | Extract clean, structured text page-by-page or across targeted page ranges from any PDF document |
| PDF Reading | get_pdf_info | Inspect PDF metadata, total page count, per-page dimensions, author, subject, creation date, and structure |
| PDF Visuals | render_pdf_page_as_image | Rasterize any PDF page into a high-resolution PNG image at custom DPI — ideal for inspecting charts, diagrams, tables, and scanned documents |
| PDF Visuals | extract_pdf_images | Extract embedded raster images from PDF pages and save to disk with pixel coordinates |
| PDF Structure | get_pdf_bookmarks | Extract the hierarchical table of contents, bookmarks, and document outline with target page links |
| PDF Forms | get_pdf_form_fields | Read interactive AcroForm form fields (text boxes, checkboxes, radio buttons, dropdowns) and their values |
| PDF Assets | extract_pdf_attachments | Extract embedded file attachments from PDF documents and save them to disk |
| PDF Links | get_pdf_hyperlinks | Extract all clickable web URLs, internal page jumps, and external document links with bounding boxes |
Instead of reading full files (~2500 tokens each), the agent gets back only the matching lines (~110 tokens) — saving up to 98% of context window per query. For files that must be read in full, use compress_code first to strip whitespace overhead and save an additional 10–20% of tokens. For PDF documentation, technical manuals, and specifications, dedicated tools extract targeted text, images, and tables without overwhelming the model context window.
If you have the .NET SDK installed (recommended for .NET developers):
dotnet tool install -g PuneethDC.DotNetSearch
Once installed, the command dotnetsearch is available globally from any terminal.
To update to the latest version in the future:
dotnet tool update -g PuneethDC.DotNetSearch
Go to the latest release and download the self-contained executable for your platform:
| Platform | File to download |
|---|---|
| Windows x64 | DotNetSearch-win-x64.exe |
| Linux x64 | DotNetSearch-linux-x64 |
| macOS ARM64 | DotNetSearch-osx-arm64 |
No .NET installation required. The runtime is bundled inside the executable.
Save it somewhere permanent, e.g.:
C:\Tools\DotNetSearch.exe/usr/local/bin/DotNetSearchOn Linux/macOS, make it executable:
chmod +x /usr/local/bin/DotNetSearch
Open (or create) your global MCP config file:
| Client | Config file location |
|---|---|
| Visual Studio | %USERPROFILE%\.mcp.json |
| VS Code + Copilot | %USERPROFILE%\.mcp.json |
| Claude Desktop | %APPDATA%\Claude\claude_desktop_config.json |
| Cursor | %USERPROFILE%\.cursor\mcp.json |
Works identically across Windows, Linux, and macOS without path differences:
{
"servers": { "DotNetSearch": { "type": "stdio", "command": "dotnetsearch" } } }
{
"servers": { "DotNetSearch": { "type": "stdio", "command": "C:\\Tools\\DotNetSearch.exe" } } }
{
"servers": { "DotNetSearch": { "type": "stdio", "command": "/usr/local/bin/DotNetSearch" } } }
dnx (Zero-Install):{
"servers": { "DotNetSearch": { "type": "stdio", "command": "dnx", "args": ["PuneethDC.DotNetSearch"] } } }
If you already have other servers in the file, just add the "DotNetSearch" block inside the existing "servers" object.
Visual Studio / VS Code:
search, search_related, decompile_type, compress_code, read_fileread_pdf_text, get_pdf_info, render_pdf_page_as_image, extract_pdf_images, get_pdf_bookmarks, get_pdf_form_fields, extract_pdf_attachments, get_pdf_hyperlinksTo make Copilot automatically prefer DotNetSearch over built-in file reading, add the instructions below to your Copilot instructions file. There are two places you can put this — repo-level (affects only that repo) or global (affects all repos).
File location:
<your-repo-root>\.github\copilot-instructions.md
This file is read by GitHub Copilot for every conversation in that repository. It is the recommended place if you want DotNetSearch to be preferred only for a specific project.
How to find or create it:
.github subfolder — if it doesn't exist, create it.github, look for copilot-instructions.md — if it doesn't exist, create the fileFile location:
| Client | Global instructions file |
|---|---|
| Visual Studio | %APPDATA%\Microsoft\VisualStudio\Copilot\copilot-instructions.md |
| VS Code + Copilot | %USERPROFILE%\.github\copilot-instructions.md |
How to find or create it:
copilot-instructions.md doesn't exist in the folder, create the fileNote: If you add instructions to both files, Copilot merges them — both will be active at the same time.
Paste the following into whichever file you chose above:
## Search Preference
When searching for code, symbols, or text in this repository, always prefer the DotNetSearch MCP tool (search and search_related) over reading full files or using built-in workspace search. DotNetSearch returns only matching lines and is significantly more token-efficient (~98% fewer tokens per query). Do not call DotNetSearch tools in parallel — run one search at a time.
When reading, analyzing, or searching PDF documents:
read_pdf_text and get_pdf_info over raw file operations.get_pdf_info to inspect total pages and document metadata.read_pdf_text with specific page ranges (startPage, endPage) to avoid token overflow.render_pdf_page_as_image to rasterize the page.get_pdf_form_fields to extract user inputs.When the user asks about a third-party or NuGet type and the source code is not available in the workspace, use the DotNetSearch MCP tool decompile_type to decompile the type from the project's referenced assemblies. Pass the short or fully qualified type name and the absolute path to the .csproj file. The project must have been built at least once before calling this tool.
When reading source files to minimize context window usage, use the DotNetSearch MCP tool compress_code — BUT ONLY for the following fully-safe languages where indentation is cosmetic and braces/keywords define scope:
C#, Java, JavaScript, TypeScript, C, C++, Kotlin, Swift, Rust, Scala, PHP, Ruby, CSS, SCSS, Less, JSON, XML
NEVER call compress_code on any other language. In particular, NEVER use it on Python, YAML, CoffeeScript, Pug/Jade, HAML, or Makefile — these are indentation-sensitive and compression WILL silently corrupt the file structure.
Before calling compress_code, check the file extension:
Pass the absolute file path. For JavaScript/TypeScript projects using 2-space indentation, set sourceIndentSize=2.
No special commands or workflow changes are needed. Just continue your normal coding tasks in Copilot Agent Mode — DotNetSearch will be used automatically whenever Copilot needs to search your codebase or inspect PDF documents.
Over time you will notice a reduction in token usage per conversation. This is because DotNetSearch returns only the matching lines (typically ~110 tokens) instead of full file contents (~2500 tokens), saving up to 98% of context window per search operation.
searchSearches a local directory for files whose content matches a keyword or natural-language query. Uses BM25 ranking with CamelCase and snake_case token expansion.
| Parameter | Type | Default | Description |
|---|---|---|---|
query | string | required | Keyword, identifier, or natural-language phrase |
repo | string | required | Absolute or relative path to the directory to search |
top_k | int | 5 | Max results to return (1–100) |
context_lines | int | 0 | Lines of context above/below each match (0–5) |
search_relatedFinds code chunks structurally similar to a specific location in a file. Use after search to explore related implementations, callers, or patterns.
| Parameter | Type | Default | Description |
|---|---|---|---|
file_path | string | required | Path to the file as returned by a prior search result |
| line | int | required | Line number (1-indexed) from a pr
Solo se muestra el principio; lee el resto en el repo