mcp-memento (Bogeymanlicitness496/mcp-memento) is an MCP server listed on the M8ven Trust Index. M8ven graded this before, but the code is no longer public at the location we read it, so we cannot re-check it. No publisher has claimed this listing.

Source no longer public

mcp-memento

Provides AI coding assistants with persistent memory storage using a local SQLite database. Enables tools to remember project details, notes, and relationships across sessions to maintain context and reduce repetitive explanations.

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Who stands behind it

Bogeymanlicitness496

Source: Glama · also listed on github_topic

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Install from

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// tools this server exposes25 tools

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

find_path_between_mementos

Find the shortest path between two mementos through relationships

get_memento_clusters

Detect clusters of densely connected mementos

get_central_mementos

Find mementos that connect different clusters (knowledge bridges)

suggest_memento_relationships

Get intelligent suggestions for relationship types between two mementos

find_memento_patterns

Find patterns in mementos and relationships Analyzes the relationship graph to detect recurring structural patterns: - Most frequent relationship types - Common memory-type pairs connected by relationships Note: patterns require multiple occurrences of the same relationship type. With small datase

analyze_memento_graph

Get comprehensive analytics and metrics for the memento graph

get_memento_network

Get the complete network structure of mementos and relationships

memento_onboarding

Get comprehensive onboarding protocol for Memento including tool usage guidance, retrieval flow optimization, and best practices. MEMENTO ONBOARDING PROTOCOL: 1. INITIALIZATION: Run memento_onboarding() at session start 2. RETRIEVAL FLOW: - Fact Check: Use search_mementos(tags=[...]) for simple

recall_mementos

Primary tool for finding mementos using natural language queries. Optimized for fuzzy matching - handles plurals, tenses, and case variations automatically. BEST FOR: - Conceptual queries ("how does X work") - General exploration ("what do we know about authentication") - Fuzzy/approximate matchin

store_memento

Store a new memento with context and metadata. Required: type, title, content. Optional: id, tags, importance (0-1), context. USE FOR: Long-term knowledge that should survive across ALL sessions. DO NOT USE FOR: Temporary session state or project-specific context. LIMITS: - title: max 500 charact

get_memento

Retrieve a specific memento by ID. Use when you have a memory_id from search results or store_memento. Set include_relationships=true (default) to see connected memories. EXAMPLE: get_memento(memory_id="abc-123")

update_memento

Update an existing memento

delete_memento

Delete a memento and all its relationships

search_mementos

Advanced search with fine-grained filters for precise retrieval of mementos. USE THIS TOOL FIRST (not recall) when searching for: - Acronyms: DCAD, JWT, MCR2, API, etc. - Proper nouns: Company names, service names, project names - Known tags: When you know the tag from previous memories - Technical

contextual_memento_search

Search only within the context of a given memento (scoped search). Two-phase process: (1) Find related memories, (2) Search only within that set. Provides semantic scoping without embeddings. WHEN TO USE: - Searching within a specific problem context - Finding solutions in related knowledge - Scop

create_memento_relationship

Link two mementos with a typed relationship. Common types: SOLVES (solution→problem), CAUSES (cause→effect), ADDRESSES (fix→error), REQUIRES (dependent→dependency), RELATED_TO (general) EXAMPLES: - create_memento_relationship(from_memory_id="sol-1", to_memory_id="prob-1", relationship_type="SOLVES

get_related_mementos

Find mementos connected to a specific memory via relationships. Filter by relationship_types (e.g., ["SOLVES"], ["CAUSES"]) and max_depth (default 1). EXAMPLES: - get_related_mementos(memory_id="prob-1", relationship_types=["SOLVES"]) - find solutions - get_related_mementos(memory_id="err-1", rela

get_memento_statistics

Get statistics about the memento database

get_recent_memento_activity

Get summary of recent memento activity for session context. Returns: memory counts by type, recent memories (up to 20), unresolved problems. EXAMPLES: - get_recent_memento_activity(days=7) - last week's activity - get_recent_memento_activity(days=30, project="/app") - last month for specific proje

search_memento_relationships_by_context

Search memento relationships by their structured context fields (scope, conditions, evidence, components)

adjust_memento_confidence

Manually adjust confidence of a relationship. Use for: - Correcting confidence scores when you know a memory is valid/invalid - Setting custom confidence based on verification - Overriding automatic decay for specific cases Examples: - adjust_memento_confidence(relationship_id="rel-123", new_confi

get_low_confidence_mementos

Find memories with low confidence scores. Use for: - Identifying potentially obsolete knowledge - Periodic cleanup and verification - Quality assurance of the knowledge base - Finding memories that need review Features: - Filter by confidence threshold (default: < 0.3) - Shows relationships causin

apply_memento_confidence_decay

Apply automatic confidence decay based on last access time. Use for: - System maintenance to keep knowledge base fresh - Applying intelligent decay rules - Monthly confidence adjustment routine Intelligent decay rules: - Critical memories (security, auth, api_key, password, critical, no_decay tags

boost_memento_confidence

Boost confidence when a memory is successfully used. Use for: - Reinforcing valid knowledge - Manual confidence increase for verified information - After successfully applying a solution - When verifying old information is still valid Usage patterns: - After successfully applying a solution → boos

set_memento_decay_factor

Set custom decay factor for specific memories. Use for: - Marking memories as "no decay" (critical information) - Adjusting decay rates based on importance - Customizing decay for specific use cases Special tags for no decay: - security, auth, api_key, password, critical, no_decay Decay factor ra

// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
configXDG_DATA_HOME
configMEMENTO_DB_PATH
configMEMENTO_PROFILE
configMEMENTO_LOG_LEVEL
configMEMENTO_ALLOW_CYCLES
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

25/25 tools missing one or more hints — find_path_between_mementos (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_memento_clusters (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_central_mementos (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +22 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tests exist

No test files found

Add tests that exercise each declared tool.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 3 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
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commit: 12973de2b429d7d208b259ad66888cbe1a69d261
code hash: 49a593c6e0204a106e4e4e0031e2e1a54d27b5ad1000478d599093b2e6161d15
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