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., "@Resurgo-MCP search my notes for 'project planning' and show what's due today"
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.
Official MCP (Model Context Protocol) server for Resurgo - your ideas rise again.
Resurgo helps you capture important information (URLs, notes, ideas) and forces them to resurface at scheduled times - via email digests, browser new tab override, and AI assistant integration. Never lose track of what matters.
Related MCP server: Open-Brain
npm install resurgo-mcp
# or
pnpm add resurgo-mcpLog in to Resurgo
Go to Settings → API
Click Create API Key
Copy your key
Add to your claude_desktop_config.json:
{
"mcpServers": {
"resurgo": {
"command": "npx",
"args": ["resurgo-mcp"],
"env": {
"RESURGO_API_KEY": "your_api_key_here"
}
}
}
}Optional: Override the API URL (for self-hosted instances):
{
"mcpServers": {
"resurgo": {
"command": "npx",
"args": ["resurgo-mcp"],
"env": {
"RESURGO_API_KEY": "your_api_key_here",
"RESURGO_API_URL": "https://your-instance.com/api"
}
}
}
}The MCP server provides 5 tools for managing your knowledge:
Search your saved items with full-text search and filters.
{
query: string; // Search term
tags?: string[]; // Filter by tags
status?: 'active' | 'parked' | 'done' | 'archived';
limit?: number; // Max results (default: 20)
}Example:
"Search my Resurgo nodes for 'react hooks' with the tag 'development'"
Get items that are due for review today (your inbox).
{
includeOverdue?: boolean; // Include overdue items (default: true)
}Example:
"Show me what's due in my Resurgo inbox today"
Save a new item with optional scheduling.
{
title: string; // Item title
note?: string; // Optional notes
url?: string; // Optional URL
tags?: string[]; // Tags for organization
resurfaceIn?: string; // When to resurface (see below)
}Scheduling options:
"tomorrow" - Resurface tomorrow at 9am
"next week" or "1 week" - In 7 days
"2 weeks" - In 14 days
"next month" or "1 month" - In 30 days
"2025-06-15" - Specific ISO date
Example:
"Save this URL to Resurgo: https://react.dev/learn with the note 'Review new hooks API' and resurface next week"
Defer an item to resurface later.
{
nodeId: string; // Item UUID
until: string; // When to resurface (same format as quick_capture)
}Example:
"Snooze this Resurgo item until tomorrow"
Mark an item as done.
{
nodeId: string; // Item UUID
}Example:
"Mark this Resurgo item as complete"
The MCP server connects to your Resurgo account via API and provides AI assistants like Claude with tools to:
Search through your saved knowledge
Capture new items during conversations
Schedule when items should resurface
Manage your inbox (snooze, complete, etc.)
This means you can have natural conversations like:
"Search my Resurgo notes about TypeScript patterns and create a new note summarizing the key points to review next week"
The AI will use the MCP tools to search, synthesize the information, and create a scheduled note automatically.
Research Management: Save articles, papers, and links during research sessions
Learning: Schedule spaced repetition for concepts you're learning
Project Planning: Capture ideas and schedule them for review at the right time
Meeting Notes: Save action items and have them resurface before deadlines
Reading List: Never lose track of articles you want to read
Node.js 20+
Active Resurgo account (sign up)
Resurgo API key (create one)
MCP-compatible AI assistant (Claude Desktop, etc.)
Issues: GitHub Issues
API Key Authentication: Secure token-based access
Scoped Access: API keys are tied to your account and can be revoked anytime
HTTPS Only: All communication encrypted in transit
MIT License - see LICENSE for details
Made with ❤️ by Code Atlantic
Mark a node as done
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action ('mark as done') but doesn't disclose behavioral traits like whether this is a mutation (implied by 'mark'), what permissions are required, if changes are reversible, side effects (e.g., triggers notifications), or response format. For a mutation tool with zero annotation coverage, this is a significant gap.
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 with zero waste. It's front-loaded with the core action and appropriately sized for a simple tool. Every word earns its place, making it easy to parse quickly.
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 tool's complexity (mutation with 1 parameter, nested object, no annotations, no output schema), the description is incomplete. It lacks details on behavior, usage context, parameter semantics, and expected outcomes. For a tool that modifies state, this minimal description leaves critical gaps for an AI agent to operate 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 description has 0 parameters explicitly mentioned, but the input schema has 1 parameter (nodeId) with 0% schema description coverage. The description implies a 'node' parameter through context, but doesn't add details beyond what's inferred. With only one parameter and no schema descriptions, the baseline is high, but the description doesn't fully compensate for the coverage gap by explaining parameter meaning or constraints.
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 'Mark a node as done' clearly states the action (mark) and resource (node) with a specific verb and object. It distinguishes from siblings like 'get_due_items' (read) or 'snooze_node' (delay), but doesn't explicitly differentiate beyond the basic action. The purpose is unambiguous but could be more specific about what 'done' means in this context.
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., node must exist, be in a certain state), exclusions (e.g., cannot mark already-done nodes), or relationships to sibling tools like 'snooze_node' for deferring completion. Usage is implied only by the action name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get items due for review (inbox items)
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets' items, implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns paginated results, or what format the output takes. This is a significant gap 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, clear sentence that directly states the tool's purpose. There is no wasted verbiage, 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 the complexity (one parameter with nested structure), no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety or performance, parameter usage, or output format, leaving the agent with insufficient information to use the tool 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 0%, with one parameter ('state') that includes a nested object property ('includeOverdue'). The description adds no information about parameters—it doesn't explain what 'state' means, how 'includeOverdue' affects results, or any other input details. With low schema coverage, the description fails to compensate, resulting in poor parameter documentation.
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 ('Get') and resource ('items due for review'), and clarifies these are 'inbox items'. However, it doesn't differentiate this tool from sibling tools like 'search_nodes' or 'snooze_node', which might also deal with items/nodes, so it doesn't reach the highest 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. It doesn't mention sibling tools like 'search_nodes' (which might search for items) or 'complete_node' (which might mark items as done), leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Save a new node with optional scheduling
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Save a new node' implies a write operation, but it doesn't mention permissions required, whether this creates permanent records, error conditions, or what happens on success. The 'optional scheduling' hint is minimal behavioral context.
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 immediately conveys the core functionality. Every word earns its place: 'Save' (action), 'new node' (resource), 'optional scheduling' (key feature). No wasted words or unnecessary elaboration.
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?
For a write operation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'saving' entails (persistence level, where saved), what the optional scheduling does, or what happens after invocation. The agent lacks crucial context for proper tool selection and 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?
The schema has 0% description coverage, but the single parameter 'state' is a nested object with well-described sub-properties (title, note, url, tags, resurfaceIn). The description mentions 'optional scheduling' which aligns with 'resurfaceIn', adding some semantic context beyond the schema's technical descriptions.
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 ('Save a new node') and the resource ('node'), with the additional feature of 'optional scheduling' distinguishing it from basic creation tools. However, it doesn't explicitly differentiate from sibling tools like 'complete_node' or 'snooze_node' which also manipulate nodes.
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 'complete_node' or 'snooze_node'. It mentions 'optional scheduling' but doesn't clarify when scheduling is appropriate versus other node operations, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search saved nodes with full-text and semantic search
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'full-text and semantic search' which gives some context about search methodology, but doesn't describe what 'saved nodes' are, how results are returned, whether there's pagination, authentication requirements, rate limits, or error conditions. For a search tool with no annotation coverage, this leaves significant behavioral gaps.
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 at just 7 words, front-loading the core functionality without any wasted words. Every element ('search', 'saved nodes', 'full-text and semantic search') contributes directly to understanding the tool's purpose. The structure is optimal for quick comprehension.
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?
For a search tool with 4 nested parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a 'saved node', how search results are structured, what 'semantic search' entails operationally, or any limitations of the search functionality. The combination of complex parameters and lack of structured metadata requires more descriptive context than provided.
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 description provides no parameter information beyond the tool name's implication of searching. With 0% schema description coverage, the description doesn't compensate by explaining what parameters are available or their purposes. However, the schema itself is well-structured with clear property descriptions for query, tags, status, and limit, establishing a baseline understanding despite the description's lack of parameter details.
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 ('search') and resource ('saved nodes'), specifying both full-text and semantic search capabilities. It distinguishes this from sibling tools like 'complete_node' or 'get_due_items' by focusing on search functionality rather than modification or retrieval of specific items. However, it doesn't explicitly differentiate from potential search alternatives within the toolset.
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?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any prerequisites, context for use, or comparisons with other tools. While sibling tools like 'quick_capture' or 'snooze_node' serve different purposes, there's no explicit direction on when search is appropriate versus those operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Defer resurfacing to a later date
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. 'Defer resurfacing' implies a mutation (snoozing), but it doesn't disclose permissions needed, whether the action is reversible, rate limits, or what happens to the node's state. It lacks details on effects like notifications or updates to due dates.
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 with no wasted words. It's front-loaded and appropriately sized for the tool's complexity, making it easy to parse quickly.
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 tool's complexity (mutation with nested parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, parameter details, or return values, leaving significant gaps for an AI agent to understand and invoke the tool correctly.
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 description has 0% schema description coverage, but it compensates by implying the purpose of the single parameter (a state object for deferral). However, it doesn't explain the nested 'nodeId' and 'until' fields or their formats. Since there's effectively 1 parameter (the state object), the baseline is high, but some semantic gaps remain.
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 'Defer resurfacing to a later date' is vague about what 'resurfacing' means and what resource is being acted upon. It doesn't clearly distinguish this from sibling tools like 'complete_node' or 'get_due_items'. While it hints at postponing something, it lacks specificity about the 'node' resource mentioned in the schema.
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?
No guidance is provided on when to use this tool versus alternatives like 'complete_node' or 'search_nodes'. The description doesn't mention prerequisites, context (e.g., when a node needs deferral), or exclusions. It's a standalone statement with no comparative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Each tool has a clearly distinct purpose with no overlap: complete_node marks nodes as done, get_due_items retrieves due items, quick_capture saves new nodes, search_nodes searches existing nodes, and snooze_node defers resurfacing. The descriptions make it easy to distinguish between creation (quick_capture), retrieval (get_due_items, search_nodes), and modification (complete_node, snooze_node) operations.
All tools follow a consistent verb_noun naming pattern with snake_case: complete_node, get_due_items, quick_capture, search_nodes, and snooze_node. The verbs are clear and appropriate (complete, get, capture, search, snooze), and the nouns consistently refer to nodes or items, creating a predictable and readable set.
With 5 tools, this server is well-scoped for managing nodes/items in a productivity or note-taking system. Each tool earns its place by covering core operations: capture (quick_capture), retrieval (get_due_items, search_nodes), and status updates (complete_node, snooze_node). The count is neither too thin nor bloated, fitting typical workflows efficiently.
The tool set provides strong coverage for a node management system, including creation, retrieval, and modification (completion and deferral). A minor gap exists in update operations for node content or metadata beyond scheduling, but agents can work around this by capturing new nodes. Core workflows like inbox review and search are well-supported, with no dead ends.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Search and manage your Dexi notes: full-text and semantic search, tags, folders, spaced repetition.
Brain dump, routines, task planning, focus, and instant thought retrieval
A self-improving memory layer. Your memory, notes, tasks and goals, remembered everywhere.
Search, extend, and act on your team's Naumu knowledge graph: notes, threads, and nodes.
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