Back to Prompt Library
implementation

Implement MCP Tool for Fast Data Lookup

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Build Low-Latency Agentic Reasoning Workloads with OpenAI o3 and Langroid MCP

Format
Text-first
Lines
1
Sections
1
Linked challenge
Build Low-Latency Agentic Reasoning Workloads with OpenAI o3 and Langroid MCP

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines
1 sections
No variables
0 checklist items
Implement a simple MCP-enabled tool for fast key-value lookups (e.g., a Redis cache client). This tool should allow Langroid agents to query and store data with minimal overhead. Provide code examples demonstrating how an agent would invoke this tool.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.