What can you do with this server?

The Geekbot MCP server enables seamless interaction with Geekbot data within LLM applications via natural language. You can: * Fetch Standups: Retrieve a list of all standups from your workspace * Fetch Reports: Retrieve standup reports with filters for standup ID, user ID, and date range * List Polls: View all available polls * Post Reports: Submit new standup reports * List Team Members: Access team member information * Retrieve Poll Results: Get data from completed polls * Generate Weekly Rollups: Create comprehensive weekly summary reports

How do I use Geekbot MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Geekbot MCP show me yesterday's standup reports for my team" 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.

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Geekbot MCP

Official

by geekbot-com

Overview Schema Related Servers Score Discussions(1)

Python

Local

Geekbot MCP

IMPORTANT

⚠️ This project is no longer maintained and has been archived

Development of this local, self-installed MCP server has stopped. We've moved to a remote, OAuth-authenticated Geekbot MCP server that requires no local install, no API key in a config file, and stays up to date automatically.

What to use instead:

Geekbot Remote MCP Server: Connect your AI assistant to Geekbot via the remote MCP server. → Setup guide
Geekbot CLI & AI Skill: Submit reports, analyse past responses, and manage standups and polls from your terminal or AI coding agent (Claude Code, Cursor, Windsurf, Copilot). → github.com/geekbot-com/geekbot-cli

This repository remains available, read-only, for reference. The instructions below are kept for historical purposes and are no longer supported.

Geekbot MCP Logo License: MIT Python 3.10+ PyPI version

Unlock your Geekbot data within your LLM applications 🚀

Geekbot MCP (Model Context Protocol) server acts as a bridge, connecting LLM client applications (like Claude, Cursor, Windsurf, etc.) directly to your Geekbot workspace. This allows you to interact with your standups, reports, and team members seamlessly within your conversations using natural language.

Related MCP server: Notion MCP Server

Key Features ✨

Access Standup and Poll Information: List all standups and polls in your Geekbot workspace. 📊
Retrieve Standup Reports and Poll Results: Fetch reports and poll results with filters for specific standups, users, or date ranges. 📄
View Team Members: Get a list of members you collaborate with in Geekbot. 👥
Post Standup Reports: Post a standup report to Geekbot. 📝

Check the video:

Alt text

Installation 💻

Manual Installation

Requires Python 3.10+ and uv.

Install Python 3.10+ (if you haven't already):
- macOS:
  brew install python@3.10
  See Homebrew Python installation guide for more details.
- Ubuntu/Debian:
  sudo apt update sudo apt install python3.10
- Windows: Download and install from Python.org.
  See Windows Python installation guide for more details.
Install uv (if you haven't already):
- macOS/Linux: In your terminal, run the following command:
  curl -LsSf https://astral.sh/uv/install.sh | sh
- Windows: In your PowerShell, run the following command:
  powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
(See uv installation docs for more options.)
Install/Upgrade Geekbot MCP:
- macOS/Linux: In your terminal, run the following command:
  uv tool install --upgrade geekbot-mcp
- Windows: In your PowerShell, run the following command:
  uv tool install --upgrade geekbot-mcp

Configuration ⚙️

After installling Geekbot MCP, you can connect it to your an LLM client desktop application (e.g., Claude Desktop, Cursor, Windsurf, etc.):

Get your Geekbot API Key: Find it in your Geekbot API/Webhooks settings 🔑.
Find your uv executable path:

Linux/macOS: In your terminal, run the following command:
```
  which uv
```

Windows: In your PowerShell, run the following command:

  (Get-Command uv | Select-Object -ExpandProperty Path) -replace '\\', '\\'

Configure your LLM client desktop application: Each LLM client that supports MCP provides a configuration file that you can edit to add Geekbot MCP server.

If you are using a different LLM client, please refer to the documentation of your client to learn how to configure the MCP server.

After you locate the configuration file, edit it to add Geekbot MCP server:

    {
      "mcpServers": {
        "geekbot-mcp": {
          "command": "UV-PATH",
          "args": [
            "tool",
            "run",
            "geekbot-mcp"
          ],
          "env": {
            "GB_API_KEY": "YOUR-API-KEY"
          }
        }
      }
    }

Make sure to replace:

UV-PATH with the path to your uv executable from step 2
YOUR-API-KEY with your Geekbot API key from step 1

Usage 💡

Once configured, your LLM client application will have access to the following tools and prompts to interact with your Geekbot data:

Tools 🛠️

list_standups

Purpose: Lists all the standups accessible via your API key. Useful for getting an overview or finding a specific standup ID.

Example Prompt: "Hey, can you list my Geekbot standups?"

Data Fields Returned:

id: Unique standup identifier.
name: Name of the standup.
channel: Associated communication channel (e.g., Slack channel).
time: Scheduled time for the standup report.
timezone: Timezone for the scheduled time.
questions: List of questions asked in the standup.
participants: List of users participating in the standup.
owner_id: ID of the standup owner.
confidential: Whether the standup is confidential.
anonymous: Whether the standup is anonymous.

list_polls

Purpose: Lists all the polls accessible via your API key. Useful for getting an overview or finding a specific poll ID.

Example Prompt: "Hey, can you list my Geekbot polls?"

Data Fields Returned:

id: Unique poll identifier.
name: Name of the poll.
time: Scheduled time for the poll.
timezone: Timezone for the scheduled time.
questions: List of questions asked in the poll.
participants: List of users participating in the poll.
creator: The poll creator.

fetch_reports

Purpose: Retrieves specific standup reports. You can filter by standup, user, and date range.

Example Prompts:

"Fetch the reports for submitted yesterday in the Retrospective."
"Show me reports from user John Doe for the 'Weekly Sync' standup."
"Get all reports submitted to the Daily Standup standup after June 1st, 2024."

Available Filters:

standup_id: Filter by a specific standup ID.
user_id: Filter reports by a specific user ID.
after: Retrieve reports submitted after this date (YYYY-MM-DD) 🗓️.
before: Retrieve reports submitted before this date (YYYY-MM-DD) 🗓️.

Data Fields Returned:

id: Unique report identifier.
reporter_name: Name of the user who submitted the report.
reporter_id: ID of the user who submitted the report.
standup_id: ID of the standup the report belongs to.
created_at: Timestamp when the report was submitted.
content: The actual answers/content of the report.

post_report

Purpose: Posts a report to Geekbot.

Example Prompt: "Hey, can you post the report for the Daily Standup standup?"

Data Fields Returned:

id: Unique report identifier.
reporter_name: Name of the user who submitted the report.
reporter_id: ID of the user who submitted the report.
standup_id: ID of the standup the report belongs to.
created_at: Timestamp when the report was submitted.
content: The actual answers/content of the report.

list_members

Purpose: Lists all team members you share standups with in your Geekbot workspace.

Example Prompt: "Who are the members in my Geekbot workspace?"

Data Fields Returned:

id: Unique member identifier.
name: Member's full name.
email: Member's email address.
role: Member's role within Geekbot (e.g., Admin, Member).

fetch_poll_results

Purpose: Retrieves specific poll results. Requires a poll id and optionally a date range.

Example Prompt: "Hey, what was decided about the new logo in Geekbot polls?"

Data Fields Returned:

total_results: Total number of results.
question_results: List of question results.

Prompts 💬

weekly_rollup_report

Purpose: Generates a comprehensive weekly rollup report that summarizes team standup responses, highlights key updates, identifies risks and mitigation strategies, outlines next steps, and tracks upcoming launches.

Tips 💡

Review Tool Usage: Make the agent ask for your explicit approval for each tool action and not allow automatic tool calls. This safety feature ensures you maintain control over sensitive operations, particularly when posting reports to Geekbot. You'll be prompted to review and approve each tool call before execution, helping prevent unintended data submissions.
Ask for preview: Before posting a report, ask the agent to preview the report and not actually post it. This will give you a chance to review the report and make sure it is correct or make changes to it before posting it to Geekbot.
Limit the volume of retrieved data: If you are using the fetch_reports tool, limit the date range to a reasonable period. This will help prevent the agent from retrieving a large amount of data and causing performance issues. Have in mind that the agent will apply limits in the number of reports it can retrieve.

Arguments:

standup_id: ID of the standup to include in the rollup report.

Development 🧑‍💻

Interested in contributing or running the server locally?

Setup Development Environment

# 1. Clone the repository
git clone https://github.com/geekbot-com/geekbot-mcp.git
cd geekbot-mcp

# 2. Install uv (if needed)
# curl -LsSf https://astral.sh/uv/install.sh | sh

# 3. Create a virtual environment and install dependencies
uv sync

Running Tests ✅

# Ensure dependencies are installed (uv sync)
pytest

Contributing 🤝

Contributions are welcome! Please fork the repository and submit a Pull Request with your changes.

License 📜

This project is licensed under the MIT License.

Acknowledgements 🙏

Built upon the Anthropic Model Context Protocol framework.
Leverages the official Geekbot API.

Available Tools

6 tools

fetch_poll_resultsB

Retrieves Geekbot poll results. Use this tool to analyze poll results or track progress of polls. This tool is usually used after the list_polls tool to get the poll id.

ParametersJSON Schema

Name	Required	Description
`poll_id`	Yes	ID of the specific standup to fetch reports for. If not provided, reports for all standups will be fetched.
`before`	No	Fetch results before this date (format: YYYY-MM-DD). This is not provided unless explicitly asked by the user.
`after`	No	Fetch results after this date (format: YYYY-MM-DD). This is not provided unless explicitly asked by the user.

TDQS

B3.3/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must cover behavioral traits. It does not mention whether the operation is read-only, what happens if the poll_id is invalid, or any side effects. This is insufficient for a retrieval tool with no structured behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: first clearly states the action, second provides a usage hint. It is front-loaded and contains no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and three parameters, the description is too brief. It does not explain the return format, pagination, error behavior, or what data is included in the results. Agents need more context to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions, but the poll_id description says 'ID of the specific standup to fetch reports for', which appears inconsistent with the tool name (polls vs standups). The tool description does not clarify or correct this, so it does not add meaningful value beyond the schema and may even mislead.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Retrieves Geekbot poll results' with a specific verb and resource, and also provides use cases (analyze results, track progress). It implies differentiation from siblings like list_polls (which lists polls) by noting it is used after list_polls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions it is 'usually used after the list_polls tool to get the poll id', providing a sequential usage hint. However, it does not explicitly compare to alternatives like fetch_reports or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

fetch_reportsA

Retrieves Geekbot standup reports. Use this tool to analyze team updates or updates from specific colleagues, track progress, or compile summaries of standup activities. This tool is usually used after the list_standups tool.

ParametersJSON Schema

Name	Required	Description
`standup_id`	No	ID of the specific standup to fetch reports for. If not provided, reports for all standups will be fetched.
`user_id`	No	ID of the specific user to fetch reports for. If not provided, reports for all members will be fetched.
`after`	No	Fetch reports after this date (format: YYYY-MM-DD)
`before`	No	Fetch reports before this date (format: YYYY-MM-DD)

TDQS

A3.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavioral traits. It only states 'Retrieves' without mentioning any potential issues like large result sets if no filters are applied, authentication requirements, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise with two sentences. The first sentence states the core purpose, and the second provides context on usage and ordering. No unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 4 optional parameters and no output schema, the description adequately covers purpose and usage hint but lacks behavioral details (e.g., default behavior when no filters are set). It is minimally sufficient but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all 4 parameters. The description does not add any additional meaning beyond the schema, so it meets the baseline without adding value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves Geekbot standup reports, uses specific verbs, and provides use cases like analyzing team updates. It distinguishes from siblings by mentioning it is used after list_standups, differentiating it from fetch_poll_results.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (to analyze standup reports) and suggests it is typically used after list_standups. However, it does not explicitly state when not to use it or mention alternatives like fetch_poll_results.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_membersA

Lists all team members participating in the standups and polls of the user. Use this tool to get information about the colleagues of the user

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A3.8/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description only implies read-only behavior. It does not disclose permissions, limits, or any side effects, failing to compensate for missing annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two brief sentences convey the purpose and usage without any unnecessary words. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 parameters, the description adequately covers what it returns and its context. Lack of output schema is acceptable for such a straightforward function.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters, the baseline is 4. The description adds no further parameter information, but none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Lists') and the resource ('team members participating in standups and polls'). It distinguishes from siblings like list_polls and list_standups by focusing on members.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides guidance to 'get information about colleagues' but lacks explicit when-not-to-use or alternatives. The sibling tools are different enough that confusion is unlikely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_pollsA

Retrieves and displays all Geekbot polls a user has access to, including their complete configuration details such as name, time, timezone, questions, participants, recurrence, anonymous, and creator.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description bears the full burden. It indicates a read operation ('Retrieves and displays'), but lacks details on side effects, pagination, or error handling. The description is adequate for a simple list but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single well-formed sentence that front-loads the purpose and includes key details. Every word earns its place; no unnecessary content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and no output schema, the description lists the fields returned, which is sufficient for understanding what the tool does. It does not cover error scenarios, but for a simple list tool, it is complete enough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no parameters (100% coverage vacuously). The description adds meaning by enumerating the configuration fields returned (name, time, timezone, etc.), which is helpful beyond the empty schema. A baseline of 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Retrieves and displays' and the resource 'all Geekbot polls a user has access to', with specific fields listed (name, time, etc.). It distinguishes from siblings like fetch_poll_results and list_standups.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that this tool is for listing polls, but it does not explicitly state when to use it over alternatives (e.g., fetch_poll_results, list_standups) or any prerequisites (e.g., user authentication). It provides clear context but no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_standupsA

Retrieves and displays all Geekbot standups a user has access to, including their complete configuration details such as name, channel, questions, participants, and schedule information. Use this tool to understand the structure of the team and the processes they use track progress and sync.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behaviors. It mentions returning configuration details but lacks details on pagination, performance, or limitations. Adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first states action and scope, second gives usage guidance. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description is mostly complete for a zero-param retrieval tool. It could mention pagination or return structure limitations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has no parameters, so the description need not add param info. Baseline 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that it retrieves all Geekbot standups with configuration details, using a specific verb+resource. It distinguishes from siblings like list_members and list_polls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a usage context ('understand structure of the team and processes') but does not explicitly compare to alternatives or give 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.

post_reportA

Posts a report to Geekbot. Use this tool to post a report to Geekbot using the context of the conversation. This tool is usually used after the list_standups tool to get the standup id and the question ids. If the context of the conversation lacks sufficient information to answer the questions of the standup, the assistant will ask for the missing information. The report should be beautifully formatted. ALWAYS type formatted reporte in the conversation for preview purposes before calling this tool.

ParametersJSON Schema

Name	Required	Description	Default
`standup_id`	Yes	ID of the specific standup to post the report to.
`answers`	Yes	An object where keys are the string representation of question IDs and values are objects containing the answer text. All questions of the standup must be included in the object.

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses the need for preview and handling of missing info, but does not explain success/failure behavior, side effects, or idempotency. Minor typo 'reporte' but not impactful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is informative but somewhat verbose with slight redundancy (first two sentences say similar things). Could be more concise while retaining key guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers workflow (list_standups associations, preview requirement, missing info handling) but lacks explanation of expected output or error conditions. Adequate but could be more complete given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage, baseline 3. Description adds value by explaining that standup_id comes from list_standups and that answers must include all question IDs, beyond the schema's description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Posts a report to Geekbot' and distinguishes from sibling tools (fetch/list operations). It specifies the verb (post) and resource (report), providing unambiguous purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states it is used after `list_standups` to obtain IDs, instructs to ask for missing information, and requires a formatted preview before calling. This provides clear when-to-use and preparatory steps.

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.

7 tool updatesv0.3.4May 6, 2026
- Addedfetch_poll_results
- Changedfetch_reports15 fields changed
  - removedInput schema / properties / after / default
```
Removed value: -null
```
  - addedInput schema / properties / after / description
```
Added value: +"Fetch reports after this date (format: YYYY-MM-DD)"
```
  - removedInput schema / properties / after / title
```
Removed value: -"After"
```
  - removedInput schema / properties / before / default
```
Removed value: -null
```
  - addedInput schema / properties / before / description
```
Added value: +"Fetch reports before this date (format: YYYY-MM-DD)"
```
  - removedInput schema / properties / before / title
```
Removed value: -"Before"
```
  - removedInput schema / properties / standup_id / default
```
Removed value: -null
```
  - addedInput schema / properties / standup_id / description
```
Added value: +"ID of the specific standup to fetch reports for. If not provided, reports for all standups will be fetched."
```
  - removedInput schema / properties / standup_id / title
```
Removed value: -"Standup Id"
```
  - removedInput schema / properties / user_id / default
```
Removed value: -null
```
  - addedInput schema / properties / user_id / description
```
Added value: +"ID of the specific user to fetch reports for. If not provided, reports for all members will be fetched."
```
  - removedInput schema / properties / user_id / title
```
Removed value: -"User Id"
```
  - changedInput schema / properties / user_id / type
```
Previous value: -"integer"New value: +"string"
```
  - addedInput schema / required
```
Added value: +[]
```
  - removedInput schema / title
```
Removed value: -"fetch_reportsArguments"
```
- Removedfetch_standups
- Addedlist_members
- Addedlist_polls
- Addedlist_standups
- Addedpost_report
2 tool updatesv1.0.0Mar 28, 2025
- First observedfetch_reports
- First observedfetch_standups

Install Server

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TDQS

A3.9/5.0

Disambiguation5/5

Each tool targets a distinct resource or action: lists for polls, standups, and members; fetches for results and reports; and a single write tool. No two tools overlap in purpose.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern using snake_case (e.g., fetch_poll_results, list_standups), making naming predictable and easy to understand.

Tool Count5/5

With 6 tools, the set is well-scoped for a Geekbot integration, covering essential read operations and one write operation without being overly large or too small.

Completeness3/5

The tool set covers listing and fetching for polls and standups, but lacks create, update, or delete operations for polls and standups, and only includes one write tool (post_report). Notable gaps exist in managing resources.

Maintenance

ActivitySlowing

ResponsivenessUnresponsive

Resources

GitHub Repository

Need Help?

Reddit Discussion

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Artificial Wit AIOAuth
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RootrOAuth
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Connect your team's living knowledge base — docs, data, issues, CRM — to Claude and ChatGPT.
RAG Systems Knowledge & Memory CRM
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