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contextstream

ContextStream MCP Server

Session

session
Read-onlyIdempotent

Manages persistent context for AI assistants by capturing decisions, lessons, and plans, enabling semantic search and tracking changes across workspaces.

Instructions

Session management operations. Actions: capture (save decision/insight), capture_lesson (save lesson from mistake), get_lessons (retrieve lessons), recall (natural language recall), remember (quick save), user_context (get preferences), summary (workspace summary), compress (compress chat), delta (changes since timestamp), smart_search (context-enriched search), decision_trace (trace decision provenance), restore_context (restore state after compaction). Plan actions: capture_plan (save implementation plan), get_plan (retrieve plan with tasks), update_plan (modify plan), list_plans (list all plans). Suggested rules actions: list_suggested_rules (view ML-generated rule suggestions), suggested_rule_action (accept/reject/modify a suggestion), suggested_rules_stats (view ML accuracy stats). Team actions (team plans only): team_decisions (team-wide decisions), team_lessons (team-wide lessons), team_plans (plans across team workspaces).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform
workspace_idNoWorkspace ID (UUID).
project_idNoProject ID (UUID).
queryNoQuery for recall/search/lessons/decision_trace
contentNoContent for capture/remember/compress
titleNoTitle for capture/capture_lesson/capture_plan
event_typeNoEvent type for capture
importanceNoInput parameter: importance.
tagsNoInput parameter: tags.
categoryNoInput parameter: category.
triggerNoWhat caused the problem
impactNoWhat went wrong
preventionNoHow to prevent in future
severityNoInput parameter: severity.
keywordsNoKeywords for matching.
sinceNoISO timestamp for delta
limitNoMaximum number of results to return.
max_tokensNoMax tokens for summary
include_decisionsNoInclude related decisions.
include_relatedNoInclude related context.
include_impactNoWhether to include impact.
session_idNoSession identifier.
code_refsNoInput parameter: code refs.
provenanceNoInput parameter: provenance.
plan_idNoPlan ID for get_plan/update_plan
descriptionNoDescription for capture_plan
goalsNoGoals for capture_plan
stepsNoImplementation steps for capture_plan
statusNoPlan status
due_atNoDue date for plan (ISO timestamp)
source_toolNoTool that generated this plan
include_tasksNoInclude tasks when getting plan
is_personalNoMark plan as personal (only visible to creator). For capture_plan/list_plans.
snapshot_idNoSpecific snapshot ID to restore (defaults to most recent)
max_snapshotsNoNumber of recent snapshots to consider (default: 1)
rule_idNoSuggested rule ID for actions
rule_actionNoAction to perform on suggested rule
modified_keywordsNoModified keywords when action is modify
modified_instructionNoModified instruction when action is modify
min_confidenceNoMinimum confidence threshold for listing rules
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false. The description adds value by revealing the tool's multi-action nature (22 distinct operations) and categorizing them into groups (Plan actions, Suggested rules actions, Team actions). This provides useful context about the tool's behavioral scope beyond what annotations convey, though it doesn't address rate limits, authentication needs, or detailed operational constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a dense, unstructured list of 22 actions with minimal grouping. It's not front-loaded with the most important information, and the wall-of-text format makes it difficult to parse. While it avoids unnecessary words, the lack of structure and prioritization reduces its effectiveness as a quick reference for an AI agent.

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?

For a complex tool with 40 parameters, 22 actions, no output schema, and rich annotations, the description is inadequate. It doesn't explain return values, error conditions, or how different actions relate to each other. The annotations cover safety aspects, but the description fails to provide the operational context needed to understand this multifaceted tool's complete behavior and integration points.

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?

With 100% schema description coverage, the input schema already documents all 40 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it only mentions that certain parameters apply to specific actions (e.g., 'query for recall/search/lessons/decision_trace'). This meets the baseline expectation when schema coverage is complete, but doesn't provide significant additional value.

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 'Session management operations' and lists 22 specific actions, which provides a general purpose. However, it's vague about what 'session management' entails and doesn't clearly distinguish this tool from sibling tools like 'memory', 'context', or 'project' that might handle related functionality. The description is more of a feature list than a clear statement of purpose.

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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'memory', 'context', 'project', and 'search' available, there's no indication of which scenarios warrant using 'session' versus those other tools. The description simply lists actions without contextual usage information.

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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