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ContextStream MCP Server

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Read-onlyIdempotent

Search workspace memory and knowledge using automatic, semantic, keyword, or pattern modes. Control output format, depth, and results count for efficient retrieval.

Instructions

Search workspace memory and knowledge. Modes: auto (recommended), semantic (meaning-based), hybrid (legacy alias for auto), keyword (exact match), pattern (regex), exhaustive (all matches like grep), refactor (word-boundary matching for symbol renaming), team (cross-project team search - team plans only), crawl (deep multi-modal search).

Output formats: full (default, includes content), paths (file paths only - 80% token savings), minimal (compact - 60% savings), count (match counts only - 90% savings).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoSearch mode (auto recommended; hybrid is a backward-compatible alias; crawl is deep multi-modal search)auto
queryYesSearch query
workspace_idNoWorkspace ID (UUID).
project_idNoProject ID (UUID).
limitNoMax results to return (default: 3)
offsetNoOffset for pagination
content_max_charsNoMax chars per result content (default: 400)
context_linesNoLines of context around matches (like grep -C)
exact_match_boostNoBoost factor for exact matches (default: 2.0)
output_formatNoResponse format: full (default), paths (80% savings), minimal (60% savings), count (90% savings)
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context about modes and output formats but does not disclose additional behavioral traits like rate limits, performance implications, or what happens to incomplete queries.

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?

Two sentences: first states purpose, second efficiently lists all relevant modes and formats. No wasted words, front-loaded.

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?

With 10 parameters and no output schema, the description covers modes and output formats but omits details on parameters like limit, offset, context_lines, etc. However, schema descriptions cover those, so overall it's fairly complete for common usage.

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?

Input schema has 100% description coverage. The description adds extra meaning for modes (e.g., 'meaning-based', 'exact match') and output formats (token savings percentages), enhancing understanding beyond schema.

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

Purpose4/5

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

The description states 'Search workspace memory and knowledge' which is a clear verb+resource. However, it does not explicitly differentiate from sibling tools like 'context' or 'memory', so it could be more distinctive.

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 provides detailed guidance on when to use each mode (e.g., 'auto recommended', 'keyword exact match', 'team only for team plans') and output formats, but does not explicitly state when not to use this tool versus alternatives.

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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