Skip to main content
Glama

memcp_peek_chunk

Read a specific chunk from a chunked context to retrieve knowledge stored in persistent memory without consuming context window tokens.

Instructions

Read a specific chunk from a chunked context.

Args:
    context_name: Context name
    chunk_index: Chunk number (0-indexed)
    start: Start line within chunk (1-indexed, 0 = from beginning)
    end: End line within chunk (1-indexed, inclusive, 0 = to end)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startNo
chunk_indexYes
context_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries full burden. It states 'Read' which implies non-destructive, but does not disclose behavior on invalid chunk_index, out-of-range start/end, or whether the context must be chunked. No mention of return format or error handling.

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?

Extremely concise: one-line purpose followed by parameter list. No fluff, front-loaded with the action. Every sentence provides necessary information.

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 is part of a chunking system, the description does not mention that the context must be chunked (likely via memcp_chunk_context) or what happens if chunk_index is out of bounds. Output schema exists but is not described; return values are not addressed. Missing optional behavior details.

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 coverage is 0%, so description must compensate. The docstring provides brief descriptions for each parameter (context_name, chunk_index, start, end), and clarifies that start/end are 1-indexed with 0 meaning from beginning/end. This adds meaning beyond the schema titles, but descriptions are minimal.

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 'Read a specific chunk from a chunked context,' specifying the verb (Read) and the resource (specific chunk). This distinguishes it from siblings like memcp_get_context (reads entire context) and memcp_chunk_context (likely manages chunks).

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?

No guidance on when to use this tool versus alternatives. The description does not mention when to use memcp_peek_chunk instead of memcp_get_context or memcp_filter_context, nor does it specify prerequisites like the context needing to be chunked first.

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/maydali28/memcp'

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