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Context Continuation MCP Server

Context Continuation MCP Server

by core3-coder
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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context_restore_session

Restore previous work context in AI development sessions by generating a restoration prompt based on specified project path, ensuring continuity after token limits.

Instructions

Generate a context restoration prompt for continuing work

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectPath": "<projectPath>"
    },
    "name": "context_restore_session"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectPathYesPath to project directory

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates a prompt but doesn't explain what the prompt contains, how it's formatted, whether it's read-only or has side effects, or any permissions or limitations. This is inadequate for a tool with potential behavioral implications.

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, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it highly concise and well-structured.

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?

Given the tool's complexity (generating a prompt for context restoration), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the prompt looks like, how it aids 'continuing work', or what behavioral traits to expect, leaving significant gaps for an agent to understand its use.

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 1 parameter with 100% description coverage ('Path to project directory'), so the schema fully documents the parameter. The description adds no additional parameter information, but with 0 parameters needing compensation and high schema coverage, the baseline is 4 as it doesn't detract from the schema's clarity.

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

Purpose3/5

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

The description states the tool 'Generate[s] a context restoration prompt for continuing work', which provides a clear verb ('Generate') and resource ('context restoration prompt'). However, it doesn't specify what format the prompt takes, what 'context restoration' entails, or how it differs from sibling tools like context_get_status or context_start_session, leaving the purpose somewhat vague.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., after a session ends), exclusions (e.g., not for initial setup), or comparisons to siblings like context_get_status for checking current state, leaving the agent with no usage context.

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

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