worksnaps-mcp
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., "@worksnaps-mcpLog 6 hours offline time to Worksnaps project 3456 task 12"
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.
@mhdd_24/worksnaps-mcp
MCP server for Worksnaps time tracking from Cursor chat. Verify your API token, list projects and tasks, and log offline time without opening the Worksnaps web UI.
Same architecture as Timelog / Flyway / Notepad++ / Caffeine / Workspace Build MCP packages.
Full documentation: docs/WIKI.md
How it works (30 seconds)
You (chat)
→ worksnaps-mcp
→ Worksnaps REST API (XML over HTTPS)
→ GET /me.xml | /projects.xml | /tasks.xml
→ POST /projects/{id}/time_entries.xml (offline time)Configure
WORKSNAPS_API_TOKEN(Profile & Settings → Web Service API in Worksnaps)Say "list Worksnaps projects" to pick a project ID
Say "list tasks for project 1234" to pick a task ID
Say "log 480 minutes to Worksnaps project 1234 task 56" with an optional comment
Related MCP server: YesDev MCP Server
Prerequisites
Requirement | Notes |
Node.js 18+ | Uses native |
Worksnaps API token | Profile & Settings → Web Service API → Show my API Token |
Project + task IDs | Use |
Install
Option A — npm (after publish)
npm install -g @mhdd_24/worksnaps-mcpOption B — npx
npx @mhdd_24/worksnaps-mcpOption C — clone and build
git clone https://github.com/Mhdd-24/Worksnaps-MCP.git
cd Worksnaps-MCP
npm install
npm run build
node dist/index.jsConfigure Cursor
Edit ~/.cursor/mcp.json:
{
"mcpServers": {
"worksnaps": {
"command": "npx",
"args": ["-y", "@mhdd_24/worksnaps-mcp"],
"env": {
"WORKSNAPS_API_TOKEN": "<your-api-token>",
"WORKSNAPS_DEFAULT_PROJECT_ID": "1234",
"WORKSNAPS_DEFAULT_TASK_ID": "5678"
}
}
}
}Local development:
"command": "node",
"args": ["C:/path/to/worksnaps-mcp/dist/index.js"]Reload MCP after saving.
Tools
Tool | Purpose |
| Resolve current user from API token ( |
| List accessible projects |
| List tasks in a project |
| Create offline time entry for yourself |
Chat examples
"Run whoami on Worksnaps"
"List Worksnaps projects"
"List tasks for Worksnaps project 3456"
"Log 6 hours offline time to Worksnaps project 3456 task 12 — comment: Sprint development"
Environment variables
Variable | Required | Purpose |
| Yes* | API token (Basic auth username; password ignored) |
| No | Default project for |
| No | Default task for |
| No | API base URL (default |
*Can be passed as token per tool call instead.
Notes
log_timecreates offline time entries (Worksnaps API: POST/projects/{project_id}/time_entries.xml).from_timestampis aligned to a 10-minute boundary (Worksnaps API requirement).Default
startHouris 9 (local time) when only a date is provided.
License
ISC
Available Tools
4 toolslist_projectsB
List Worksnaps projects the current user can access (GET /projects.xml).
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | Worksnaps API token. Optional if WORKSNAPS_API_TOKEN is set. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only mentions the HTTP method (GET) and access scope. It does not disclose pagination, rate limits, error handling, or output format, which are important for a list operation.
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 sentence that efficiently conveys the core action. It is not verbose, though could include more context without significant 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 simple list tool with no output schema, the description provides the essential purpose but omits details about the response structure, ordering, or any limitations. It is minimally adequate.
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 100% with a single parameter 'token' already described in the schema. The description adds no further semantics, but the baseline of 3 is appropriate since the schema does the work.
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 identifies the verb 'list', resource 'Worksnaps projects', and scope 'the current user can access'. It also provides the underlying API endpoint. This distinguishes it from sibling tools like list_tasks and log_time.
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 usage is implied by the description but no explicit guidance is given on when to use this tool over alternatives, nor any prerequisites or exclusions. The agent must infer context from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_tasksB
List tasks in a Worksnaps project (GET /projects/{projectId}/tasks.xml).
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | Worksnaps API token. Optional if WORKSNAPS_API_TOKEN is set. | |
| projectId | Yes | Worksnaps project ID. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states the basic operation (listing tasks) without mentioning side effects, permissions, rate limits, or error states. This is insufficient for a tool with no annotation support.
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 no wasted words. It includes the API endpoint for clarity, though it could be slightly more front-loaded. Overall efficient.
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 simplicity (2 params, no output schema, no annotations), the description provides the basic purpose but lacks details on usage context, error handling, or return format. 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?
Schema coverage is 100%, so both parameters are documented in the schema. The description adds no extra meaning beyond referencing the projectId in the endpoint. Baseline 3 is appropriate as the description does not enhance 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 clearly states the action ('List tasks'), the resource ('in a Worksnaps project'), and provides the API endpoint. It distinguishes itself from sibling tools like 'list_projects' (lists projects) and 'log_time' (logs time).
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 does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Usage is implied by the action, but no direct comparison with siblings is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
log_timeA
Log offline time to Worksnaps for yourself (POST /projects/{projectId}/time_entries.xml). Requires projectId, taskId, and minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Entry date YYYY-MM-DD. Defaults to today (local). from_timestamp aligns to a 10-minute boundary. | |
| token | No | Worksnaps API token. Optional if WORKSNAPS_API_TOKEN is set. | |
| taskId | No | Worksnaps task ID. Optional if WORKSNAPS_DEFAULT_TASK_ID is set. | |
| comment | No | Optional work description (user_comment). | |
| minutes | Yes | Duration in minutes for the offline time entry. | |
| projectId | No | Worksnaps project ID. Optional if WORKSNAPS_DEFAULT_PROJECT_ID is set. | |
| startHour | No | Optional local hour (0-23) on the entry date for from_timestamp. Defaults to 9. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It indicates the tool creates a time entry (POST), which implies mutation. It mentions that date defaults to today and startHour defaults to 9, but does not disclose side effects, error handling, rate limits, or what happens on duplicate entries. This is minimal but acceptable for a simple logging tool.
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 sentence of 20 words, front-loading the purpose and then specifying requirements. Every word is meaningful, with no redundancy.
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 tool with 7 parameters, 1 required, and no output schema, the description provides the core purpose and required fields. However, it does not explain the return value (e.g., success status or entry ID), error cases, or constraints like maximum minutes. The context is somewhat complete but lacks details that would help the agent handle edge cases.
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 baseline is 3. The description adds the context of 'offline time' and the HTTP method, but restates that projectId, taskId, and minutes are required, while the schema shows projectId and taskId as optional (with defaults). This slight inconsistency reduces clarity. The added value is marginal, so a 3 is appropriate.
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: logging offline time to Worksnaps. It specifies the HTTP method and resource (POST /projects/{projectId}/time_entries.xml) and lists required parameters. It is distinct from the sibling tools, which are all read/list operations.
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 explicit prerequisites (requires projectId, taskId, and minutes), which guides the agent on what must be supplied. However, it does not discuss when to use this tool versus alternatives, nor does it mention conditions where it should not be used. It is adequate but could be more comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
whoamiA
Resolve the current Worksnaps user from the API token (GET /me.xml). Returns user id, login, name, and email.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No | Worksnaps API token. Optional if WORKSNAPS_API_TOKEN is set. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses the GET method, endpoint, and return values (user id, login, name, email). It does not mention potential errors or side effects, but the behavior is largely clear.
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?
Two sentences efficiently convey purpose, method, and return fields with no wasted words.
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 with one optional parameter and no output schema; the description adequately covers the return fields and operation.
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 parameter token is fully documented. The description adds no extra semantics beyond confirming the token is used for authentication.
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 resolves the current user from the API token, specifies the HTTP method and endpoint, and lists the return fields. This distinguishes it from sibling tools like list_projects, which focus on different resources.
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 usage when the user identity is needed, but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.
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.
4 tool updates
v1.0.0- First observed
list_projects - First observed
list_tasks - First observed
log_time - First observed
whoami
TDQS
Each tool targets a distinct resource: projects, tasks, time entries, and user identity. There is no ambiguity between them.
Most tools follow a verb_noun pattern (list_projects, list_tasks, log_time). 'whoami' deviates slightly but is still an imperative verb. Overall consistent.
With 4 tools, the server is focused and well-scoped for its purpose. Each tool serves a clear need without bloat.
The tool surface lacks read operations for logged time entries and lacks CRUD for projects and tasks. Users cannot retrieve, update, or delete time entries, which is a significant gap.
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
Manage projects, tasks, time tracking, and team collaboration through natural language.
Track time on usetimebook.com - start/stop timers, log entries, list projects/clients.
- AurentiaOAuthfr.aurentia
Your Aurentia workspace — projects, CRM, tasks, deliverables — in Claude, Cursor or any MCP client.
Track billable time from your AI chat: timers, entries, reports, CSV export. All data stays local.
Related MCP Servers
- AlicenseBqualityDmaintenanceEnables natural language time tracking and reporting for Harvest, including automatic leave requests, project/task matching, and date parsing.5125MIT
- AlicenseNot gradedqualityDmaintenanceAutomatically logs developer work hours and manages tasks, projects, requirements, and daily reports through YesDev project management platform. Enables programmers to track time and update project progress through conversational AI in development tools like Cursor and VSCode.185MIT
- AlicenseBqualityCmaintenanceConnects Cursor/Claude to your Vaiz workspace, enabling search and management of tasks, projects, documents, milestones, and team members through natural language.33781MIT
- FlicenseNot gradedqualityDmaintenanceEnables logging time to Tempo (Jira time tracker) via natural language in Claude Desktop or OpenCode.-
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/Mhdd-24/WorkSnaps-MCP'
If you have feedback or need assistance with the MCP directory API, please join our Discord server