Consult LLM▌
by raine
Consult LLM escalates complex reasoning tasks to advanced models with code context, git diffs, and detailed cost trackin
Escalates complex reasoning tasks to more powerful language models (OpenAI o3, Google Gemini 2.5 Pro, DeepSeek Reasoner) by forwarding markdown prompts with code context and git diffs, returning responses with detailed cost tracking.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers stuck on complex debugging issues
- / Code reviews requiring advanced reasoning
- / Escalating tasks when Claude hits limits
capabilities
- / Query advanced AI models with file context
- / Include git diffs for code review
- / Track consultation costs in real-time
- / Resume multi-turn conversations across requests
- / Monitor active consultations via TUI dashboard
what it does
Lets Claude consult more powerful AI models (GPT-5, Gemini Pro, DeepSeek) when handling complex reasoning tasks, especially for debugging code issues. Includes detailed cost tracking and multi-turn conversations.
about
Consult LLM is a community-built MCP server published by raine that provides AI assistants with tools and capabilities via the Model Context Protocol. Consult LLM escalates complex reasoning tasks to advanced models with code context, git diffs, and detailed cost trackin It is categorized under ai ml, developer tools.
how to install
You can install Consult LLM in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Consult LLM is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
consult-llm-mcp
An MCP server that lets Claude Code consult stronger AI models (GPT-5.2, Gemini 3.1 Pro, DeepSeek Reasoner) when Sonnet has you running in circles and you need to bring in the heavy artillery. Supports multi-turn conversations.
> Still getting this error after your fix. Ask gemini
E5108: Error executing lua: attempt to call method 'child' (a nil value)
⏺ Let me consult Gemini to understand the Neovim treesitter API changes:
⏺ consult-llm:consult_llm (MCP)(prompt: "Neovim plugin broken due to treesitter
API changes...", files: ["lua/testonly.lua"],
model: "gemini-2.5-pro")
⎿ The issue is that iter_matches() can return nil nodes in newer Neovim
versions. Switch to iter_captures() which never returns nil nodes, and use
named_child(0) instead of child(0) to get only meaningful syntax nodes.
… +93 lines (ctrl+r to expand)
⏺ The LLM identified the issue - iter_matches() API changed. Switching to
iter_captures() approach now.
Quick start · Configuration · Monitor TUI · Changelog
Features
- Query powerful AI models (GPT-5.2, Gemini 3.1 Pro, DeepSeek Reasoner) with relevant files as context
- Direct queries with optional file context
- Include git changes for code review and analysis
- Comprehensive logging with cost estimation
- Monitor TUI: Real-time dashboard for watching active consultations
- Gemini CLI backend: Use the
geminiCLI to take advantage of free quota - Codex CLI backend: Use the
codexCLI for OpenAI models - Cursor CLI backend: Use the
cursor-agentCLI to route GPT and Gemini models through a single tool - Multi-turn conversations: Resume CLI sessions
across requests with
thread_id - Web mode: Copy formatted prompts to clipboard for browser-based LLM services
- Less is more: Single MCP tool to not clutter the context
Quick start
-
Add to Claude Code (choose one):
With npx (no install required):
claude mcp add consult-llm \ -e OPENAI_API_KEY=your_key \ -e GEMINI_API_KEY=your_key \ -- npx -y consult-llm-mcpWith binary (no Node.js required):
curl -fsSL https://raw.githubusercontent.com/raine/consult-llm-mcp/main/scripts/install.sh | bash claude mcp add consult-llm \ -e OPENAI_API_KEY=your_key \ -e GEMINI_API_KEY=your_key \ -- consult-llm-mcpFor global availability across projects, add
<details> <summary>Using multiple API keys or CLI backends</summary>--scope user.
</details>claude mcp add consult-llm \ -e OPENAI_API_KEY=your_openai_key \ -e GEMINI_API_KEY=your_gemini_key \ -e DEEPSEEK_API_KEY=your_deepseek_key \ -e CONSULT_LLM_GEMINI_BACKEND=gemini-cli \ -- npx -y consult-llm-mcp -
Verify connection with
/mcp:❯ 1. consult-llm ✔ connected -
Ask a question:
"Consult Gemini about how to fix the race condition in server.ts"
Example workflows
Some real-world examples. Click to expand.
<details> <summary>Explain the problem, and tell CC to consult a smarter LLM</summary> <Some long explanation of the issue here>
Consult LLM for assistance, use gemini
⏺ I see the issue! The problem is that the frontend is trying to use the hint
for "isn't" but the server generated a hint for "isn't it" (the full phrase).
This is a mismatch between how the frontend segments text and how the server
generates hints.
Let me consult the LLM to get assistance on this segmentation mismatch issue.
⏺ Write(hint-segmentation-issue.md)
⎿ Wrote 53 lines to hint-segmentation-issue.md
# Hint Segmentation Mismatch Issue
## Problem Description
There's a mismatch between how the frontend segments text for clickable
words and how the backend generates hints. This causes hint unlocking to
fail when the segments don't match exactly.
## Example Case
**Original Text**: "Hello! Nice weather, isn't it?"
… +43 lines (ctrl+r to expand)
⏺ consult-llm:consult_llm (MCP)(model: "gemini-2.5-pro", files: ["/project/hint
-segmentation-issue.md","/project/web/src/compo
nents/HintsText.tsx","/project/web/src/utils/hi
nts.ts","/project/server/src/routes/public/hint
s.ts","/project/server/src/llm/hints.ts"])
⎿ An excellent analysis of the problem. The root cause has been correctly
identified: a race condition within the `handleConfirmGenerateHints`
function in `HintsText.tsx`. The component state updates in the background
after `await generateHints()`, but the function continues executing with a
stale `activeSegment` variable, causing it to request a hint for a smaller
text segment ( e.g., "isn't") instead of the full, newly-available hint
phrase (e.g., "isn't it").
… +607 lines (ctrl+r to expand)
⏺ Perfect! The LLM identified the core issue - there's a race condition in
handleConfirmGenerateHints where the function uses stale state after async
operations. The solution is to re-target the hint key after generation to
find the correct matching hint.
Let me implement this solution:
⏺ Update Todos
⎿ ☐ Fix hint segmentation mismatch by implementing smarter hint key
targeting in handleConfirmGenerateHints
</details>
<details>
<summary>Using web mode to copy prompts to clipboard for browser-based LLMs</summary>
> I need help implementing a -b/--background flag for my Rust CLI. Use consult LLM with web mode
⏺ I'll use web mode to copy the formatted prompt to your clipboard so you can
paste it into any browser-based LLM service.
⏺ consult-llm:consult_llm (MCP)(prompt: "What is the best approach to implement a
-b/--background flag for the "workmux add" command that
creates a tmux window in the background without switching to
it?
The current implementation automatically switches to
the newly created window via `tmux::select_window()` in the
`setup_environment()` function. I need to make this behavior
conditional based on a flag passed from the
CLI.
Consider:
1. Where should the background flag be
threaded through the call chain?
2. Should I modify the
existing SetupOptions struct or add a parameter?
3. What's
the most maintainable approach given the codebase
structure?
4. Are there any edge cases to consider (e.g.,
should select_pane also be conditional)?", files:
["src/cli.rs","src/workflow.rs","src/tmux.rs"], web_mode:
true)
⎿ ✓ Prompt copied to clipboard!
Please paste it into your browser-based LLM service and share the response
here before I proceed with any implementation.
Note: File paths were included:
- src/cli.rs
- src/workflow.rs
- src/tmux.rs
> [User pastes the response from the external LLM]
⏺ Thank you! Based on the recommendations, I'll now implement the solution...
This is useful when:
- You want to use a free browser-based LLM service instead of API credits
- You prefer a specific LLM's web interface
- You want to review the full prompt before submitting it
⏺ Fixed! Added nil checks for both node and child and updated the iter_matches call to handle the newer API properly.
> Still not working:
E5108: Error executing lua /Users/raine/code/testonly.nvim/lua/testonly.lua:92: attempt to call method 'child' (a nil value)
stack traceback:
/Users/raine/code/testonly.nvim/lua/testonly.lua:92: in function 'reset_all_exclusive'
/Users/raine/code/testonly.nvim/lua/testonly.lua:110: in function 'reset_all_exclusive'
[string ":lua"]:1: in main chunk
Ask gemini
⏺ Let me consult with a more powerful AI to understand the current Neovim treesitter API changes:
⏺ consult-llm:consult_llm (MCP)(prompt: "I'm debugging a Neovim plugin that's broken due to treesitter API changes. The error is "attempt to call method 'child' (a nil value)" on line 92. The
code is trying to access child nodes from treesitter matches but the API seems to have changed in newer Neovim versions.
Here's the problematic
code:
```lua
for _, match, _ in parsed_query:iter_matches(root, bufnr, start_row, end_row) do
for id, node in pairs(match) do
local name =
parsed_query.captures[id]
if name == "call" and node then
local child = node:child(0) -- ERROR HERE
if child then
local text = vim.treesitter.get_node_text(child, bufnr)
-- ... rest of logic
end
end
end
end
```
What's the
correct way to iterate over treesitter query matches and access child nodes in current Neovim versions? What API changes should I be aware of?", files:
["/Users/raine/code/testonly.nvim/lua/testonly.lua"])
⎿ Problem
-------
---
FAQ
- What is the Consult LLM MCP server?
- Consult LLM is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Consult LLM?
- This profile displays 65 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★65 reviews- ★★★★★Shikha Mishra· Dec 28, 2024
We evaluated Consult LLM against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Mia Rao· Dec 16, 2024
Useful MCP listing: Consult LLM is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Noah Tandon· Dec 12, 2024
Consult LLM is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Charlotte Gupta· Dec 12, 2024
Consult LLM reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Charlotte Bansal· Dec 8, 2024
Consult LLM is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Ganesh Mohane· Dec 4, 2024
Consult LLM reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Soo Martin· Dec 4, 2024
Useful MCP listing: Consult LLM is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Nov 23, 2024
I recommend Consult LLM for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Henry Abebe· Nov 23, 2024
Strong directory entry: Consult LLM surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Maya Brown· Nov 19, 2024
We evaluated Consult LLM against two servers with overlapping tools; this profile had the clearer scope statement.
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