mcp-ollama-qdrant
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OLLAMA_URL | No | Ollama base URL | http://192.168.X.X:11434 |
| QDRANT_URL | No | Qdrant base URL | http://192.168.X.X:6333 |
| EMBED_MODEL | No | Embedding model | qwen3-embedding:8b |
| COLLECTION_NAME | No | Collection name | agent_scenarios |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| save_memoryA | Save a new document or scenario outcome into the vector DB. |
| save_memoriesB | Save multiple documents into the vector DB in one batch. All texts are embedded in a single Ollama call and upserted together. metadata (JSON string or object) is applied to every document. If collection is given, the memories are stored there (created automatically if missing). |
| search_memoryA | Search the vector DB for past documents/scenarios semantically similar to a query. |
| update_memoryA | Update an existing memory (point) in place under the same ID. |
| delete_memoryA | Delete a stored memory (point) from the vector DB by ID. |
| list_collectionsA | List all collections currently present in Qdrant. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool targets a distinct operation: save (single), save_memories (batch), search, update, delete, and list_collections. The single-vs-batch split between save_memory and save_memories is explicitly distinguished in the descriptions, so an agent can reliably choose.
All tools follow a consistent snake_case verb_noun pattern (save_memory, search_memory, update_memory, delete_memory, save_memories, list_collections). The only variation, list_collections, reflects a genuinely different resource (collections vs memories), not an inconsistent style.
Six tools is well-scoped for a vector-DB memory server, covering the full point lifecycle plus collection listing without redundancy. Nothing feels padded or missing at the count level.
Core memory lifecycle (create, batch create, search, update, delete) and collection listing are all present, making the surface largely complete. Minor gaps remain: no get_memory-by-ID retrieval and no collection deletion/creation management beyond implicit auto-creation.