Skip to main content
Glama
ContextPulse

ContextPulse

Official
by ContextPulse
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

about

Discover ContextPulse: its purpose, installation steps, and connection endpoints. Ideal for agents needing a quick overview before using screen, voice, or activity tools.

Instructions

Return a summary of ContextPulse: what it captures, how to install, and where to connect.

Returns a multi-line string describing the daemon, its data sources, the local MCP endpoint, and primary documentation URLs.

USE WHEN: an agent needs to learn what ContextPulse is or where to find docs before deciding to use other ContextPulse tools. NOT FOR: fetching live screen/voice/activity data — use get_screenshot, get_screen_text, get_recent_voice, or get_activity_summary for that. ALTERNATIVES: open GITHUB_URL or SITE_URL directly for human-readable docs.

BEHAVIOR: pure read of static metadata. No side effects, no auth, no rate limits. Safe to call from any agent at any time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • glama/server.py:40-60 (handler)
    The 'about' tool handler function. Registered with @mcp_app.tool(), returns a static metadata string describing ContextPulse including installation URL, site URL, and local MCP endpoint.
    def about() -> str:
    """Return a summary of ContextPulse: what it captures, how to install, and where to connect.

    Returns a multi-line string describing the daemon, its data sources, the local
    MCP endpoint, and primary documentation URLs.

    USE WHEN: an agent needs to learn what ContextPulse is or where to find docs
    before deciding to use other ContextPulse tools.
    NOT FOR: fetching live screen/voice/activity data — use get_screenshot,
    get_screen_text, get_recent_voice, or get_activity_summary for that.
    ALTERNATIVES: open GITHUB_URL or SITE_URL directly for human-readable docs.

    BEHAVIOR: pure read of static metadata. No side effects, no auth, no rate
    limits. Safe to call from any agent at any time.
    """
    return (
        "ContextPulse is a local desktop daemon that captures screen (with OCR), "
        "voice (Whisper), keyboard/mouse activity, and clipboard, then exposes the "
        "data to AI agents over MCP. All processing is local; no cloud, no telemetry. "
        f"Install: {GITHUB_URL}  Site: {SITE_URL}  Local MCP endpoint: {LOCAL_ENDPOINT}"
    )
  • glama/server.py:39-40 (registration)
    Registration of the 'about' tool via the @mcp_app.tool() decorator on line 39.
    @mcp_app.tool()
def about() -> str:
  • glama/server.py:21-23 (helper)
    Constants GITHUB_URL, SITE_URL, and LOCAL_ENDPOINT used by the about tool to construct its return string.
    GITHUB_URL = "https://github.com/ContextPulse/contextpulse"
SITE_URL = "https://contextpulse.ai"
LOCAL_ENDPOINT = "http://localhost:8420/mcp"

Tool Definition Quality

A4.9/5.0
Behavior5/5

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

Despite no annotations, the description fully discloses behavior: pure read of static metadata, no side effects, no auth, no rate limits, safe to call anytime. This is comprehensive and goes beyond what annotations would typically provide.

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?

Well-structured with clear sections (USE WHEN, NOT FOR, ALTERNATIVES, BEHAVIOR). Every sentence adds value, no redundancy. Concise yet comprehensive.

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

Completeness5/5

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

Given zero parameters, an output schema exists, and the description fully explains what is returned: a multi-line string with daemon info, data sources, endpoint, and URLs. No gaps remain.

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?

No parameters exist (0 params, baseline 4). The description adds value by explaining the output content, but there is no parameter information to add since there are none.

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 returns a summary of ContextPulse, including what it captures, installation, and connection info. It uses specific verbs and resources, and distinguishes itself from sibling tools by explicitly stating what it is not for and listing alternatives.

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?

Explicit USE WHEN and NOT FOR sections guide the agent on when to use this tool versus alternatives. It clearly states when to use (to learn about ContextPulse) and when not to (for live data), and names alternative tools.

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

Install Server

Other Tools

Latest Blog Posts

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/ContextPulse/contextpulse'

If you have feedback or need assistance with the MCP directory API, please join our Discord server