@mseep/atlas-mcp-server
Version:
A Model Context Protocol (MCP) server for ATLAS, a Neo4j-powered task management system for LLM Agents - implementing a three-tier architecture (Projects, Tasks, Knowledge) to manage complex workflows.
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text/typescript
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { z } from 'zod';
import { createToolExample, createToolMetadata, registerTool } from '../../../types/tool.js';
import { atlasAddKnowledge } from './addKnowledge.js';
import { AtlasKnowledgeAddSchemaShape } from './types.js';
export const registerAtlasKnowledgeAddTool = (server: McpServer) => {
registerTool(
server,
"atlas_knowledge_add",
"Adds a new knowledge item or multiple items to the system with domain categorization, tagging, and citation support",
AtlasKnowledgeAddSchemaShape,
atlasAddKnowledge,
createToolMetadata({
examples: [
createToolExample(
{
mode: "single",
projectId: "proj_ms_migration",
text: "GraphQL provides significant performance benefits over REST when clients need to request multiple related resources. By allowing clients to specify exactly what data they need in a single request, GraphQL eliminates over-fetching and under-fetching problems common in REST APIs.",
domain: "technical",
tags: ["graphql", "api", "performance", "rest"],
citations: ["https://graphql.org/learn/best-practices/", "https://www.apollographql.com/blog/graphql/basics/graphql-vs-rest/"]
},
`{
"id": "know_graphql_benefits",
"projectId": "proj_ms_migration",
"text": "GraphQL provides significant performance benefits over REST when clients need to request multiple related resources. By allowing clients to specify exactly what data they need in a single request, GraphQL eliminates over-fetching and under-fetching problems common in REST APIs.",
"tags": ["graphql", "api", "performance", "rest"],
"domain": "technical",
"citations": ["https://graphql.org/learn/best-practices/", "https://www.apollographql.com/blog/graphql/basics/graphql-vs-rest/"],
"createdAt": "2025-03-23T10:11:24.123Z",
"updatedAt": "2025-03-23T10:11:24.123Z"
}`,
"Add technical knowledge about GraphQL benefits with citations and tags"
),
createToolExample(
{
mode: "bulk",
knowledge: [
{
projectId: "proj_ui_redesign",
text: "User interviews revealed that 78% of our customers struggle with the current checkout flow, particularly the address entry form which was described as 'confusing' and 'overly complex'.",
domain: "business",
tags: ["user-research", "checkout", "ux-issues"]
},
{
projectId: "proj_ui_redesign",
text: "Industry research shows that automatically formatting phone numbers and credit card fields as users type reduces error rates by approximately 25%. Implementing real-time validation with clear error messages has been shown to decrease form abandonment rates by up to 40%.",
domain: "technical",
tags: ["form-design", "validation", "ux-patterns"],
citations: ["https://baymard.com/blog/input-mask-form-fields", "https://www.smashingmagazine.com/2020/03/form-validation-ux-design/"]
}
]
},
`{
"success": true,
"message": "Successfully added 2 knowledge items",
"created": [
{
"id": "know_checkout_research",
"projectId": "proj_ui_redesign",
"text": "User interviews revealed that 78% of our customers struggle with the current checkout flow, particularly the address entry form which was described as 'confusing' and 'overly complex'.",
"tags": ["user-research", "checkout", "ux-issues"],
"domain": "business",
"citations": [],
"createdAt": "2025-03-23T10:11:24.123Z",
"updatedAt": "2025-03-23T10:11:24.123Z"
},
{
"id": "know_form_validation",
"projectId": "proj_ui_redesign",
"text": "Industry research shows that automatically formatting phone numbers and credit card fields as users type reduces error rates by approximately 25%. Implementing real-time validation with clear error messages has been shown to decrease form abandonment rates by up to 40%.",
"tags": ["form-design", "validation", "ux-patterns"],
"domain": "technical",
"citations": ["https://baymard.com/blog/input-mask-form-fields", "https://www.smashingmagazine.com/2020/03/form-validation-ux-design/"],
"createdAt": "2025-03-23T10:11:24.456Z",
"updatedAt": "2025-03-23T10:11:24.456Z"
}
],
"errors": []
}`,
"Add multiple knowledge items with mixed domains and research findings"
)
],
requiredPermission: "knowledge:create",
returnSchema: z.union([
// Single knowledge response
z.object({
id: z.string().describe("Knowledge ID"),
projectId: z.string().describe("Project ID"),
text: z.string().describe("Knowledge content"),
tags: z.array(z.string()).describe("Categorical labels"),
domain: z.string().describe("Knowledge domain"),
citations: z.array(z.string()).describe("Reference sources"),
createdAt: z.string().describe("Creation timestamp"),
updatedAt: z.string().describe("Last update timestamp")
}),
// Bulk creation response
z.object({
success: z.boolean().describe("Operation success status"),
message: z.string().describe("Result message"),
created: z.array(z.object({
id: z.string().describe("Knowledge ID"),
projectId: z.string().describe("Project ID"),
text: z.string().describe("Knowledge content"),
tags: z.array(z.string()).describe("Categorical labels"),
domain: z.string().describe("Knowledge domain"),
citations: z.array(z.string()).describe("Reference sources"),
createdAt: z.string().describe("Creation timestamp"),
updatedAt: z.string().describe("Last update timestamp")
})).describe("Created knowledge items"),
errors: z.array(z.object({
index: z.number().describe("Index in the knowledge array"),
knowledge: z.any().describe("Original knowledge data"),
error: z.object({
code: z.string().describe("Error code"),
message: z.string().describe("Error message"),
details: z.any().optional().describe("Additional error details")
}).describe("Error information")
})).describe("Creation errors")
})
]),
rateLimit: {
windowMs: 60 * 1000, // 1 minute
maxRequests: 20 // 20 requests per minute (higher than project creation as knowledge items are typically smaller)
}
})
);
};