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Read Context

read_context

Retrieve saved project context by topic name, or list all available topics when no topic is specified, to access durable decisions and conventions across sessions.

Instructions

Read a saved OpenContext topic, or list all available topics when no topic is provided.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoOptional topic name in snake_case or kebab-case. Omit to list all saved topics.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It transparently reveals the two modes of operation and the optional parameter behavior, and the verb 'read' implies a non-mutating operation. It does not discuss error handling or return format, but that is a minor gap for such a simple read tool.

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 with no filler. The primary read behavior is front-loaded, and the list-all alternative is stated compactly.

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?

This is a low-complexity tool with one optional parameter, and the description adequately covers both invocation modes. There is no output schema, and the description does not detail the return shape or error behavior, but an agent still has enough information to invoke the tool correctly in either mode.

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?

Schema description coverage is 100%, and the schema already documents that 'topic' is an optional snake_case/kebab-case name and that omitting it lists all topics. The description adds little beyond what the schema already provides, so the baseline score of 3 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 states a specific verb ('read') and resource ('saved OpenContext topic'), and explicitly covers the alternative list-all behavior. It is clearly distinguishable from the sibling tool 'save_context'.

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 clearly indicates when to call the tool: provide a topic to read it, or omit the topic to list available topics. It does not explicitly name 'save_context' as the alternative for writing, but the read-vs-save contrast makes the usage obvious.

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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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/slxca/opencontext'

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