quickmemo-mcp
QuickMemo MCP Server πβ‘
QuickMemo MCP is a sleek, minimalistic, and unique Model Context Protocol (MCP) server that provides AI assistants with a fast, structured scratchpad and context memo engine.
Built cleanly using the official Python MCP SDK, QuickMemo showcases all three core MCP primitivesβTools, Resources, and Promptsβin an elegant, zero-bloat codebase
π Key Highlights
β‘ Minimalist & Zero-Bloat: Under 150 lines of clean, readable Python code.
π― All 3 MCP Primitives:
Tools: Save, list, search, filter, retrieve, and delete context memos.
Resources: Real-time markdown digest (
memo://all) and dynamic telemetry (memo://stats).Prompts: Ready-to-use prompt templates for note reviews and daily standup generation.
π Zero Configuration Required: Instant out-of-the-box local persistent JSON storage (
~/.quickmemo/memos.json).π Marketplace & Registry Ready: Preconfigured with
smithery.yamlandDockerfilefor one-click deployment to Smithery and Glama.π Universal Compatibility: Works seamlessly with Claude Desktop, Cursor, Antigravity IDE, Windsurf, and custom MCP clients.
Related MCP server: mindmap-mcp-server
π Project Structure
quickmemo-mcp/
βββ docs/ # Learning documentation & reports
β βββ EXISTING_MCP_EXPERIENCE.md # Hands-on write-up evaluating Context7 & Playwright
β βββ MCP_FUNDAMENTALS.md # Complete MCP protocol & architecture guide
βββ src/
β βββ quickmemo/ # MCP Server package (<150 LOC)
β βββ __init__.py # Package exports
β βββ __main__.py # Executable entrypoint
β βββ server.py # Core server (Tools, Resources, Prompts)
βββ tests/
β βββ demo_client.py # Live interactive demonstration script
β βββ test_server.py # Pytest unit & integration test suite
βββ Dockerfile # Containerized deployment manifest
βββ LICENSE # MIT License
βββ pyproject.toml # Package configuration & dependencies
βββ README.md # Quickstart & user documentation
βββ smithery.yaml # Smithery registry manifestπ Architecture Overview
+-------------------------------------------------------------------------------+
| MCP CLIENT |
| (Claude Desktop / Cursor IDE / Antigravity / Custom AI) |
+-------------------------------------------------------------------------------+
β²
β JSON-RPC 2.0 (stdio)
βΌ
+-------------------------------------------------------------------------------+
| QUICKMEMO MCP SERVER |
| |
| [TOOLS] [RESOURCES] [PROMPTS] |
| β’ add_memo β’ memo://all (Digest) β’ review_notes |
| β’ list_memos β’ memo://stats (JSON) β’ daily_standup |
| β’ search_memos |
| β’ get_memo / delete_memo |
+-------------------------------------------------------------------------------+
β
βΌ
Local JSON Storage Engine
(~/.quickmemo/memos.json)π οΈ MCP Primitives Catalog
1. Tools (Model-Controlled Functions)
Tool Name | Parameters | Description |
|
| Saves a new memo or snippet with optional category and tags. |
|
| Lists saved memos with optional category and tag filtering. |
|
| Retrieves full content and metadata for a specific memo. |
|
| Performs keyword search across title, content, tags, and category. |
|
| Deletes a memo by ID. |
| None | Empties the memo store. |
2. Resources (Dynamic Context Streams)
Resource URI | MIME Type | Description |
|
| Formatted dynamic markdown digest of all stored memos. |
|
| Real-time statistics (total memos, categories breakdown, tag distribution). |
3. Prompts (Pre-Engineered Workflow Templates)
Prompt Name | Arguments | Description |
|
| Synthesizes saved memos into key takeaways and an actionable checklist. |
| None | Converts recent memos into a standard 3-part daily standup report. |
π‘ AI Assistant Workflows & Use Cases
π§ Multi-Step Code Refactoring Scratchpad:
The LLM stores tentative architecture decisions and checklist items as memos (
category: "refactor").Allows long-horizon task continuity without overflowing working memory.
π Session Handover & Context Preservation:
Before ending a chat session, ask the AI: "Save a summary memo of today's progress and active blockers."
Start the next session with "Retrieve memos tagged 'blockers' to resume work."
π Real-Time Daily Standup Generation:
Trigger the
daily_standupprompt to instantly consolidate team notes, bug findings, and feature progress into a formatted report.
π Quickstart & Installation
Option 1: Local Setup with uv (Recommended)
# Clone the repository
git clone https://github.com/Abdullah-Zafarr/quickmemo-mcp.git
cd quickmemo-mcp
# Install dependencies and package in editable mode
uv pip install -e .
# Run test suite
uv run pytest -v
# Run the interactive demo
uv run python tests/demo_client.pyOption 2: Running Directly via CLI
# Run server over stdio
quickmemoπ Client Configuration
Claude Desktop
Add QuickMemo to your claude_desktop_config.json:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"quickmemo": {
"command": "uvx",
"args": ["--from", "quickmemo", "quickmemo"]
}
}
}Cursor IDE
Add to .cursor/mcp.json in your workspace:
{
"mcpServers": {
"quickmemo": {
"command": "quickmemo"
}
}
}Antigravity IDE
Add to your project's .agents/mcp_config.json or global MCP settings:
{
"mcpServers": {
"quickmemo": {
"command": "quickmemo"
}
}
}Windsurf & VS Code (Roo Code / Continue)
Add QuickMemo under your MCP server settings:
{
"mcpServers": {
"quickmemo": {
"command": "uv",
"args": ["run", "quickmemo"]
}
}
}βοΈ Deploying to Smithery / Glama
This repository is pre-configured for the Smithery registry with smithery.yaml and Dockerfile.
Install via Smithery CLI
npx -y @smithery/cli install quickmemo --client claudeManual Registry Deployment
Push your repository to GitHub.
Visit Smithery.ai and sign in.
Import your GitHub repository. Smithery automatically detects
smithery.yamland deploys your MCP server.
π§ͺ Testing
Run the automated test suite:
uv run pytest -vOutput:
tests/test_server.py::TestMemoStore::test_add_and_get PASSED [ 12%]
tests/test_server.py::TestMemoStore::test_list_and_filter PASSED [ 25%]
tests/test_server.py::TestMemoStore::test_search PASSED [ 37%]
tests/test_server.py::TestMemoStore::test_delete_and_clear PASSED [ 50%]
tests/test_server.py::TestServerTools::test_tool_workflow PASSED [ 62%]
tests/test_server.py::TestServerTools::test_clear_memos_tool PASSED [ 75%]
tests/test_server.py::TestServerResourcesAndPrompts::test_resources PASSED [ 87%]
tests/test_server.py::TestServerResourcesAndPrompts::test_prompts PASSED [100%]
============================== 8 passed in 1.10s ==============================βοΈ Environment Configuration & Storage Customization
By default, QuickMemo persists memos at ~/.quickmemo/memos.json. You can customize the storage path by setting the QUICKMEMO_STORAGE environment variable:
# Custom storage path example
export QUICKMEMO_STORAGE="/path/to/my_custom_memos.json"
quickmemoβ Troubleshooting & FAQs
Server not connecting in Claude Desktop or Cursor?
Ensure
uvorquickmemois available in your system'sPATH.Check that the path to
quickmemois executable and python version >= 3.10 is installed.
Where are my memos stored?
Run the
memo://statsresource in your client to view the exact activestorage_path.
How to run tests locally?
Execute
uv run pytest -vfrom the repository root to verify all 8 unit & integration tests pass.
π Deliverables & Learning Documentation
π Existing MCP Hands-On Evaluation:
docs/EXISTING_MCP_EXPERIENCE.mdπ MCP Architecture & Fundamentals Guide:
docs/MCP_FUNDAMENTALS.mdπ» Interactive Live Demo Script:
tests/demo_client.pyβοΈ Smithery Configuration:
smithery.yaml
π License
MIT License Β© 2026 QuickMemo MCP Contributors.
Available Tools
6 toolsadd_memoA
Save a new context memo, snippet, or idea with optional category and tags.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | ||
| title | Yes | ||
| content | Yes | ||
| category | No | general |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 conveys that this is a write/create action but does not describe return values, duplicate handling, persistence behavior, or any side effects beyond the implied save. It also mostly restates what the schema already exposes.
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?
A single sentence with no filler; the key action ('Save a new') and scope ('context memo, snippet, or idea') are front-loaded, and optional modifiers are included succinctly. Every part earns its place.
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 simple creation tool with an output schema available, the description plus input schema is nearly sufficient: required title/content and optional category/tags are covered. It lacks explicit sibling routing and behavior details, but those are handled in other dimensions, and the tool's complexity is low.
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 0%, so the description must compensate. It adds that category and tags are optional and frames the content as a context memo, snippet, or idea. However, it does not explain the meaning or expected format of the required title and content parameters beyond their obvious names.
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 states a specific action ('Save'), a concrete resource (a new context memo/snippet/idea), and the optional category/tags. It clearly distinguishes this creation tool from the list/get/search/delete/clear sibling tools, even without naming them.
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 phrase 'Save a new ...' implies this tool is for adding new memos rather than retrieving or managing existing ones, but it does not explicitly state when to prefer this tool over alternatives or mention any exclusion criteria. Usage context is implied, not spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
clear_memosA
Clear all stored memos (use with caution).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It clearly discloses that the operation clears all stored memos and flags it as destructive via 'use with caution,' but it does not mention irreversibility, confirmation behavior, or the resulting state.
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 front-loaded sentence with no wasted words. 'Clear all stored memos' states the action immediately, and 'use with caution' adds a valuable warning without bloat.
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 zero-parameter tool with an output schema, the description covers the essential action and scope. It could mention whether the operation is reversible or requires confirmation, but the simple interface means nothing critical is missing for invoking it.
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 tool has zero parameters, so there is no parameter semantics burden on the description. The baseline of 4 applies because no parameter documentation is needed.
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 uses a specific verb ('Clear') and identifies the resource ('all stored memos'), making the scope clear. It is distinct from the per-item delete_memo sibling because it targets everything, though it doesn't explicitly name that alternative.
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?
There is no explicit guidance on when to use this tool versus delete_memo, list_memos, or search_memos. 'Use with caution' is a warning rather than a usage condition or exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_memoA
Delete a specific memo by ID.
| Name | Required | Description | Default |
|---|---|---|---|
| memo_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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 behavior disclosure. It names the resource being removed but does not state whether deletion is permanent or irreversible, what effects might cascade, or whether any confirmation is required.
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?
One short, front-loaded sentence with no filler. It states the action and target efficiently, and every word earns its place.
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?
The tool is simple and an output schema exists, so return-value documentation is not needed here. However, for a destructive operation with no annotations, the description should at least note irreversibility and the contrast with clear_memos; it currently gives only the bare invocation.
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 phrase 'by ID' maps to the single memo_id parameter, which is enough for a one-parameter tool. However, it adds little beyond the schema's own 'Memo Id' title, and with 0% schema description coverage the description does not meaningfully enrich parameter understanding.
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 uses the verb 'delete' with a clear object ('a specific memo') and selection criterion ('by ID'). This clearly distinguishes it from list/get/search operations and especially from clear_memos, which targets all memos.
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 implies that the tool is for removing one memo chosen by ID, but it does not explicitly state when to use this versus clear_memos. No prerequisites, exclusions, or alternative conditions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_memoA
Retrieve the full details and content of a specific memo by ID.
| Name | Required | Description | Default |
|---|---|---|---|
| memo_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description alone indicates this is a safe read operation that returns full memo content, but it doesn't disclose behavior when the ID doesn't exist, whether permissions are required, or whether the response shape differs from list_memos. These are common gaps for a getter.
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?
A single, front-loaded sentence states the action, resource, and distinguishing scope without any filler or redundancy. Every word contributes to understanding what the tool does.
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 simple one-parameter getter with an output schema, the description provides the essential retrieval semantics. It lacks explicit differentiation from search_memos and error-behavior details, but those are minor for this straightforward tool.
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 description explicitly ties memo_id to 'by ID', so the agent knows the parameter selects the memo to retrieve. This adds minimal meaning beyond the parameter name and satisfies the basic expectation for a single self-explanatory parameter.
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 uses a specific verb ('Retrieve') and names a clear resource ('full details and content of a specific memo by ID'). This distinguishes get_memo from list_memos and search_memos: it targets one memo by its identifier rather than returning a collection or matching a query.
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 implies the tool is for fetching a single memo when the memo_id is already known, but it doesn't explicitly say when to prefer get_memo over search_memos or list_memos. No alternative routing or exclusion is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_memosA
List saved memos with optional category and tag filtering.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | ||
| category | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. 'List' strongly suggests a read-only operation with no side effects, which is helpful. However, it does not disclose ordering, pagination, filter match semantics, or whether the results are scoped to the current user.
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 concise sentence with the action and resource up front. Every word adds meaning and there is no redundant or filler content.
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?
The output schema exists, so return values do not need to be described in detail. However, with no annotations and a potentially overlapping sibling tool search_memos, the description is thin on when to choose this tool and how filtering behaves. It is adequate but leaves gaps.
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 input schema has no property descriptions, so the description must compensate. It names category and tag filtering and indicates they are optional, which matches the schema. But it adds no detail about accepted formats, exact-match behavior, or how multiple filters combine.
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 uses a specific verb ('List') and resource ('saved memos'), making the core purpose clear. It also mentions optional category and tag filtering. However, it does not explicitly differentiate this tool from the sibling search_memos, which could have overlapping use cases.
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 implies that the tool is for retrieving saved memos, optionally filtered by category and tag. It provides no explicit guidance about when to use list_memos versus search_memos or other sibling tools, so the usage context is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_memosA
Search memos by keyword across title, content, tags, and category.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden and does add meaningful context: it specifies that query matches multiple fields and is keyword-oriented, not an exact ID lookup. It omits details like case sensitivity or partial-match semantics, but for a read-only search tool the field scope is the key behavior.
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 entire description is one dense, front-loaded sentence that names the action, target, and applicable fields with no filler or repetition of the schema.
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 one-parameter search tool with an output schema present, the description provides the core semantic needed to invoke it correctly. Missing pieces (match semantics, sibling routing) are relatively minor or already penalized in the usage dimension, so the definition is reasonably complete.
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 coverage is 0%, so the description must give meaning to the single query parameter. It does so by defining query as a keyword and enumerating the fields searched, which compensates for the schema's lack of description.
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 uses a specific verb ('Search') and a clear resource ('memos') with an exact scope: matches across title, content, tags, and category. This clearly conveys the operation and distinguishes it from sibling tools like list_memos or get_memo.
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 keyword-search use case is implied, but the description never explicitly positions it against siblings such as list_memos (for unfiltered listing) or get_memo (for retrieving one memo). There is no when-to-use or when-not-to-use guidance.
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.
6 tool updates
v0.1.0- First observed
add_memo - First observed
clear_memos - First observed
delete_memo - First observed
get_memo - First observed
list_memos - First observed
search_memos
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose: create, list, get, search, delete, and clear. No two tools overlap in functionality, so an agent can easily select the correct one.
All tool names follow the verb_noun pattern consistently (add_memo, list_memos, get_memo, search_memos, delete_memo, clear_memos). The naming is uniformly snake_case with clear verbs and a common noun.
Six tools is well-scoped for a memo management server. Each tool covers a core operation without being excessive or too sparse.
The tool surface covers create, read (list/get/search), and delete (single and all). The only noticeable gap is the lack of an update or edit operation, which could be a minor limitation but does not interrupt the main workflow.
Maintenance
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