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Forgetful

Forgetful

by ScottRBK
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

discover_forgetful_tools

Discover available tools, optionally filtered by category

Instructions

Discover available tools, optionally filtered by category

Returns enough information for LLMs to call tools directly without needing how_to_use.

Args: category: Optional category filter (user, memory, project, code_artifact, document, entity, linking) ctx: FastMCP Context (automatically injected)

Returns: Dictionary with: - tools_by_category: Tools grouped by category - total_count: Total number of tools - categories_available: List of available categories - filtered_by: Category filter applied (if any)

All Available Tools

User Tools - User profile and preferences

  • get_current_user: Get authenticated user info

  • update_user_notes: Store user preferences/notes

Memory Tools - Atomic knowledge storage (<400 words per memory)

  • create_memory: Store a single concept with auto-linking to similar memories (supports provenance tracking)

  • query_memory: Semantic search across memories (use query_context for better ranking)

  • get_memory: Retrieve memory by ID

  • update_memory: Modify memory fields (PATCH semantics, supports provenance tracking)

  • link_memories: Manually connect related memories bidirectionally

  • unlink_memories: Remove link between memories

  • mark_memory_obsolete: Soft-delete with audit trail and optional superseded_by

  • unobsolete_memory: Restore a memory previously marked obsolete

  • get_recent_memories: Get newest memories (timeline view)

Provenance Tracking (optional fields for create_memory/update_memory):

  • source_repo, source_files, source_url: Track where knowledge came from

  • confidence: Reliability score (0.0-1.0) for AI-generated content

  • encoding_agent, encoding_version: Track which agent/version created the memory

Project Tools - Organize memories by context/scope

  • create_project: Create project container (development, personal, work, etc.)

  • get_project: Retrieve project details

  • list_projects: List all projects with optional status/repo filter

  • update_project: Modify project metadata

  • delete_project: Remove project (memories preserved)

Code Artifact Tools - Reusable code snippets and patterns

  • create_code_artifact: Store code with language, tags, project link

  • get_code_artifact: Retrieve code artifact by ID

  • list_code_artifacts: List artifacts with project/language/tags filter

  • update_code_artifact: Modify artifact fields

  • delete_code_artifact: Remove artifact

Document Tools - Long-form content (>300 words)

  • create_document: Store detailed docs, analysis, guides

  • get_document: Retrieve document by ID

  • list_documents: List documents with project/type/tags filter

  • update_document: Modify document fields

  • delete_document: Remove document

Entity Tools - Real-world entities (people, orgs, devices)

  • create_entity: Create entity with type, aka (aliases), notes

  • get_entity: Retrieve entity by ID

  • list_entities: List entities with project/type/tags filter

  • search_entities: Text search by name or aka (aliases)

  • update_entity: Modify entity fields

  • delete_entity: Remove entity (cascades links)

  • link_entity_to_memory: Connect entity to memory

  • unlink_entity_from_memory: Remove entity-memory link

  • link_entity_to_project: Connect entity to project (organizational grouping)

  • unlink_entity_from_project: Remove entity-project link

  • get_entity_memories: Get all memories linked to entity

  • get_memory_entities: Get all entities linked to memory

  • create_entity_relationship: Create relationship (part_of, depends_on, works_for, etc.)

  • get_entity_relationships: Get relationships for entity

  • update_entity_relationship: Modify relationship

  • delete_entity_relationship: Remove relationship

Workflow

  1. Call discover_forgetful_tools() to see this catalog

  2. Call execute_forgetful_tool(tool_name, {args}) to run any tool

  3. If needed, call how_to_use_forgetful_tool(tool_name) for full parameter docs

Input Schema

NameRequiredDescriptionDefault
categoryNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the response shape and notes that ctx is auto-injected rather than a user-supplied argument, but it never states that the call is side-effect-free, whether any permissions/auth are required, or whether the catalog is cached or live. Since an output schema already exists, some of the Returns block is redundant rather than additive.

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

Conciseness4/5

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

Front-loaded with purpose, then Args, Returns, catalog, Workflow — a predictable order with no filler prose. The full tool catalog is long and partly duplicates the output schema, but for a discovery tool it is close to the payload itself and aids selection.

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 one optional parameter, an output schema, and complete value enumeration plus workflow routing, an agent has everything needed to call it correctly. Minor gaps: invalid-category behavior and confirmation that no state is mutated.

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?

Schema description coverage is 0% and the schema only types category as string|null with no enum, so the description's enumeration (user, memory, project, code_artifact, document, entity, linking) is the only source of valid values and is genuinely load-bearing. It stops short of saying what happens with an unrecognized value or whether the match is case-sensitive.

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?

States a specific verb and resource ('Discover available tools') plus the optional scope ('filtered by category'). The embedded catalog and Workflow section make the boundary with execute_forgetful_tool and how_to_use_forgetful_tool explicit, so an agent can distinguish all three without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The Workflow block gives an explicit when/when-not: call this first to see the catalog, then execute_forgetful_tool to run, then how_to_use_forgetful_tool only if parameter docs are needed. It also justifies skipping the sibling ('Returns enough information for LLMs to call tools directly without needing how_to_use').

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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