Code Snippet Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Code Snippet Servercreate a Python snippet for sorting a list with title 'Quick Sort Example'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Code Snippet Server
Overview
Code Snippet Server is a Model Context Protocol (MCP) server designed to manage and store code snippets across different programming languages. It provides a flexible and extensible way to create, list, and delete code snippets using a standardized server interface.
Related MCP server: Trello Knowledge MCP Server
Features
Create code snippets with title, language, and code
List snippets with optional filtering by language or tag
Delete snippets by their unique ID
Localization support
Persistent local storage
Prerequisites
Node.js (18.x, 20.x, or 22.x)
npm
Installation
git clone git@github.com:ngeojiajun/mcp-code-snippets.git
npm run build
npm link
# Or you can do
npx @ngeojiajun/code-snippet-serverUsage
The server exposes three primary tools:
1. Create Snippet
Create a new code snippet with a title, language, and code.
Parameters:
title(required): Name of the snippetlanguage(required): Programming languagecode(required): The actual code snippettags(optional): Array of tags for categorization
2. List Snippets
Retrieve a list of snippets with optional filtering.
Parameters:
language(optional): Filter snippets by programming languagetag(optional): Filter snippets by tag
3. Delete Snippet
Remove a snippet from storage.
Parameters:
id(required): Unique identifier of the snippet to delete
Development
Build
npm run buildLint
npm run lintContributing
Any PRs are welcome
Available Tools
3 toolscreate_snippetC
Create a snippet (specify title, language, and code)
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Code snippet | |
| language | Yes | Programming language | |
| tags | No | Snippet tags | |
| title | Yes | Snippet title |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a snippet but doesn't explain what happens after creation (e.g., where the snippet is stored, if it's private or public, or any side effects like notifications). This leaves significant gaps in understanding the tool's behavior beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the main action ('Create a snippet') and specifies key parameters. It avoids unnecessary words, but could be slightly more structured by explicitly noting optional parameters or usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a creation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, error handling, or what the tool returns upon success. For a mutation operation, more context is needed to guide effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the input schema already documents all parameters (title, language, code, tags) with descriptions. The description adds minimal value by listing required parameters but doesn't provide additional context like format examples or constraints beyond what the schema offers, aligning with the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a snippet') and specifies the required components ('specify title, language, and code'), which distinguishes it from sibling tools like 'delete_snippet' and 'list_snippets'. However, it doesn't explicitly mention the optional 'tags' parameter, making it slightly less specific than a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_snippets' or 'delete_snippet'. It lacks context about prerequisites, such as authentication or workspace setup, and doesn't indicate when this tool is appropriate compared to other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_snippetC
Delete a snippet (specify ID)
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ID of snippet to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action without behavioral details. It doesn't disclose that this is a destructive operation (implied by 'Delete'), whether it's reversible, what permissions are needed, or what happens on success/failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single, clear sentence that front-loads the essential information. There is zero wasted text, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a destructive tool with no annotations and no output schema, the description is incomplete. It lacks crucial context like behavioral effects, error handling, or return values, leaving significant gaps for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'id' parameter fully. The description adds no additional meaning beyond what's in the schema, such as format examples or constraints, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and target resource ('a snippet'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'create_snippet' or 'list_snippets' beyond the obvious verb difference, missing explicit comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing snippet ID), exclusions, or comparisons to siblings like 'list_snippets' for finding IDs first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_snippetsC
List snippets (can filter by language or tags)
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Filter by specific language | |
| tag | No | Filter by specific tag |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'List snippets' which implies a read-only operation, but doesn't address permissions, pagination, rate limits, or what happens if no filters are applied. This leaves significant gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose and filtering options. There is no wasted language or unnecessary elaboration, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error conditions, or behavioral traits like pagination or permissions. For a list tool with filtering, more context is needed to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the input schema already documents both parameters ('language' and 'tag') with clear descriptions. The description adds minimal value by mentioning filtering by language or tags, but doesn't provide additional syntax, format details, or usage examples beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('List') and resource ('snippets'), and mentions filtering capabilities. However, it doesn't explicitly differentiate from sibling tools like 'create_snippet' or 'delete_snippet' beyond implying it's a read operation, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'create_snippet' or 'delete_snippet'. It mentions filtering options but doesn't specify contexts, prerequisites, or exclusions for usage, leaving the agent without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
v1.0.0- First observed
create_snippet - First observed
delete_snippet - First observed
list_snippets
TDQS
Each tool has a clearly distinct purpose: create_snippet for creation, delete_snippet for deletion, and list_snippets for listing with optional filtering. There is no overlap or ambiguity between these operations.
All tool names follow a consistent verb_noun pattern (create_snippet, delete_snippet, list_snippets) using snake_case throughout. This makes the set predictable and easy to understand.
With only 3 tools, the set feels thin for a snippet management server. While it covers basic operations, it lacks tools for updating snippets or retrieving a single snippet by ID, which are common needs in such domains.
The server provides create, delete, and list operations, but there are notable gaps: no update_snippet tool to modify existing snippets and no get_snippet tool to retrieve a specific snippet by ID. This limits functionality and may cause agent workarounds.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
A MCP server built for developers enabling Git based project management with project and personal…
An MCP server that used to create notes
An MCP server that provides congressional transcripts
Related MCP Servers
- AlicenseBqualityFmaintenanceMCP Server for running code snippet and show the result.11,366245MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that utilizes Trello as a knowledge base for storing, searching, and retrieving code snippets and notes. It enables full CRUD operations and organized categorization of information using Trello boards and labels.247MIT
- FlicenseNot gradedqualityDmaintenanceAn extended MCP server for managing code snippets, performing code analysis, and handling deployments via Render and GitHub. It enables users to perform code reviews, track issues, and manage service operations through natural language interactions.-
- FlicenseAqualityDmaintenanceAn MCP server that wraps the rustypaste API, allowing users to upload text, files, and URLs to a rustypaste instance. It supports features such as single-use links, file expiration, and URL shortening.747-
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ngeojiajun/mcp-code-snippets'
If you have feedback or need assistance with the MCP directory API, please join our Discord server