Graphiti Memory MCP Server (mjunaidca/graphiti_memory_mcp_server) is an MCP server listed on the M8ven Trust Index. It scores 69 out of 100, grade C. It declares 8 tools. No publisher has claimed this listing.

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C
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69/100

Graphiti Memory MCP Server

Enables AI agents to manage and query a temporally-aware knowledge graph memory, supporting episode tracking, entity relationships, and semantic search via MCP tools.

→ mjunaidca/graphiti_memory_mcp_server· listed on glama

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Limited view: static analysis for Python is partially covered.

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Who stands behind it

mjunaidca

Source: Glama

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Install from

Glamanot scored here

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.
🔐
You'll be asked for 3 credentials: OPENAI_API_KEY, AZURE_OPENAI_EMBEDDING_API_KEY, NEO4J_PASSWORD
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// 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.
configSEMAPHORE_LIMITEpisode processing concurrency. See [Concurrency and LLM Provider 429 Rate Limit Errors](#concurrency-and-llm-provider-429-rate-limit-errors)
configMODEL_NAMEOpenAI model name to use for LLM operations.
configSMALL_MODEL_NAMEOpenAI model name to use for smaller LLM operations.
configAZURE_OPENAI_ENDPOINTOptional Azure OpenAI LLM endpoint URL
configAZURE_OPENAI_API_VERSIONOptional Azure OpenAI LLM API version
configAZURE_OPENAI_DEPLOYMENT_NAMEOptional Azure OpenAI LLM deployment name
configAZURE_OPENAI_USE_MANAGED_IDENTITYOptional use Azure Managed Identities for authentication
🔐 secretOPENAI_API_KEYOpenAI API key (required for LLM operations)
configLLM_TEMPERATURETemperature for LLM responses (0.0-2.0).
configEMBEDDER_MODEL_NAME
configAZURE_OPENAI_EMBEDDING_ENDPOINTOptional Azure OpenAI Embedding endpoint URL
configAZURE_OPENAI_EMBEDDING_API_VERSIONOptional Azure OpenAI API version
🔐 secretAZURE_OPENAI_EMBEDDING_API_KEYOptional Azure OpenAI Embedding deployment key (if other than OPENAI_API_KEY)
configNEO4J_URIURI for the Neo4j database (default: bolt://localhost:7687)
configNEO4J_USERNeo4j username (default: neo4j)
🔐 secretNEO4J_PASSWORDNeo4j password (default: demodemo)
configMCP_SERVER_HOST
// 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

8/8 tools missing one or more hints — add_memory (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); search_memory_nodes (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); search_memory_facts (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +5 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.

Tool inputs are validated

7/8 tool handlers declare input schemas (88%)

Declare an inputSchema with zod/joi/yup on every tool definition.

License file

No license file

Add a LICENSE file (MIT, Apache-2.0, etc.).

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 5 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/mjunaidca/graphiti_memory_mcp_server)](https://m8ven.ai/mcp/mjunaidca/graphiti_memory_mcp_server)
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commit: 8b2bae1b42b732df715c8cd9e224772381c3371f
code hash: 1e7bf2c0ba11a5863af54246dec2f21d6f1ebd326506d2640e9e2615d8d4d4fa
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