MCP Ollama Consult Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OLLAMA_BASE_URL | No | The Ollama endpoint URL | http://localhost:11434 |
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| consult_ollamaB | Consult with Ollama AI models for architectural decisions, code reviews, and design discussions. Supports sequential chaining of consultations for complex multi-step reasoning. |
| list_ollama_modelsA | List all available Ollama models on the local system (installed or cloud-based) |
| compare_ollama_responsesB | Compare responses from multiple Ollama models on the same prompt to get diverse perspectives |
| remember_contextB | Store context for use in future consultations within the same session |
| sequential_consultation_chainB | Run a sequence of consultations where each consultant builds on previous responses, enabling complex multi-step reasoning. |
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 5 tools
The purposes of list_ollama_models and remember_context are distinct, but consult_ollama, compare_ollama_responses, and sequential_consultation_chain heavily overlap. All three involve querying models, differing mainly in whether responses are combined or chained, which could lead to agent confusion.
Tools mostly follow a snake_case verb_noun pattern (list_ollama_models, remember_context, compare_ollama_responses), but 'sequential_consultation_chain' breaks the verb-first pattern with an adjective-noun structure. Also, 'consult_ollama' is a general verb that overlaps with others, making the naming less distinctive.
With only 5 tools, the server is well-scoped and each tool seems to have its place, though the overlap among core consultation tools slightly reduces the necessity of having three separate ones. Still, it's a small, manageable set that fits the server's purpose.
The server covers a typical consultation workflow: listing available models, querying them, comparing responses, chaining consultations, and maintaining context. A minor gap is the lack of a tool to explicitly clear context or manage sessions, which agents might need for long-running interactions.