Tokenlab MCP Server vs Ncp
A side-by-side look at the Tokenlab MCP Server and Ncp MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Tokenlab MCP Server for aggregators work as a local process; choose Ncp for aggregators as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Tokenlab MCP Server when
- You need dedicated capabilities in the Aggregators domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
TOKENLAB_API_BASE, TOKENLAB_API_KEY, TOKENLAB_MCP_TOOL_PROFILE, TOKENLAB_MCP_SCHEMA_MODE, TOKENLAB_REQUEST_TIMEOUT_MS, TOKENLAB_MCP_MAX_FILE_BYTES, TOKENLAB_MCP_INLINE_BYTES, TOKENLAB_ARTIFACT_DIR. - You want tools like
cancel_task, create_3d_model, create_anthropic_message.
Choose Ncp when
- You need dedicated capabilities in the Aggregators domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
sequentialthinking.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Aggregators | Aggregators |
| Quality signal | 64/100 · Good | 69/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | API key required | No auth required |
| Pricing | Free | Free |
| Required env vars | TOKENLAB_API_BASETOKENLAB_API_KEYTOKENLAB_MCP_TOOL_PROFILETOKENLAB_MCP_SCHEMA_MODETOKENLAB_REQUEST_TIMEOUT_MSTOKENLAB_MCP_MAX_FILE_BYTESTOKENLAB_MCP_INLINE_BYTESTOKENLAB_ARTIFACT_DIR | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 100 |
| Directory activity | 3 views 0 installs 0 upvotes | 4 views 0 installs 0 upvotes |
| Tools | 31 | 1 |
| Full listing | View Tokenlab MCP Server | View Ncp |
Tools & capabilities
Tokenlab MCP Server tools 31
cancel_taskCancel async task Cancels a queued asynchronous task when cancellation is supported for the selected task. Cancellation currently supports queued Seedance video tasks (`seedance-1.5-pro`, `seedance-2.0`, and `seedance-2.0-fast`) while they are still waiting to run. Tasks that are already processing, completed, failed, expired, or unsupported are not cancelled.create_3d_modelCreate 3D model generation task Creates a 3D model generation task using Tripo3D. Returns a task ID for polling.create_anthropic_messageCreate message (Anthropic-compatible) Creates a model response using Anthropic's native request format. Supports Claude models with vision and streaming. **Authentication:** Use `x-api-key` header or `Authorization: Bearer` header.create_chat_completionCreate an OpenAI-compatible chat completion. For inline image_url data URLs, declare the byte-accurate image MIME type. The MCP boundary corrects recognized PNG, JPEG, WebP, and GIF payloads declared as application/octet-stream and rejects unrecognized generic binary image payloads before sending a billable request.create_embeddingCreate embeddings Creates an embedding vector representing the input text.create_gemini_contentGenerate content (Gemini-compatible) Generates content using the native Gemini GenerateContent shape. This route is exposed only when the model details advertise Gemini requests and a same-protocol route is currently available. ProtoJSON lowerCamelCase and original proto snake_case field names are preserved. Unknown fields are forwarded best-effort and support is determined by the selected provider. **Authentication:** Use `?key=` query parameter, `x-goog-api-key` header, or `Authorization: Bearer` header.create_imageCreate image Creates an image given a prompt.create_image_fileCreate image Creates an image given a prompt.create_multimodal_embeddingCreate multimodal embeddings Creates embeddings for multimodal input items. Text input is generally available; image input may require feature enablement.create_musicCreate music generation task Creates a music generation task using Suno. Returns a task ID for polling.create_responseCreate response (OpenAI Responses API) Creates a response using the native OpenAI Responses API shape. The model details must advertise the Responses request format and a same-protocol route must be currently available; model names and providers do not imply availability. Unknown request fields are forwarded on a best-effort basis and remain subject to the selected provider's support.create_speechCreate speech Generates audio from the input text (Text-to-Speech).- +19 more on the listing page
Ncp tools 1
sequentialthinkingA detailed tool for dynamic and reflective problem-solving through thoughts. This tool helps analyze problems through a flexible thinking process that can adapt and evolve. Each thought can build on, question, or revise previous insights as understanding deepens. When to use this tool: - Breaking down complex problems into steps - Planning and design with room for revision - Analysis that might need course correction - Problems where the full scope might not be clear initially - Problems that require a multi-step solution - Tasks that need to maintain context over multiple steps - Situations where irrelevant information needs to be filtered out Key features: - You can adjust total_thoughts up or down as you progress - You can question or revise previous thoughts - You can add more thoughts even after reaching what seemed like the end - You can express uncertainty and explore alternative approaches - Not every thought needs to build linearly - you can branch or backtrack - Generates a solution hypothesis - Verifies the hypothesis based on the Chain of Thought steps - Repeats the process until satisfied - Provides a correct answer Parameters explained: - thought: Your current thinking step, which can include: * Regular analytical steps * Revisions of previous thoughts * Questions about previous decisions * Realizations about needing more analysis * Changes in approach * Hypothesis generation * Hypothesis verification - nextThoughtNeeded: True if you need more thinking, even if at what seemed like the end - thoughtNumber: Current number in sequence (can go beyond initial total if needed) - totalThoughts: Current estimate of thoughts needed (can be adjusted up/down) - isRevision: A boolean indicating if this thought revises previous thinking - revisesThought: If is_revision is true, which thought number is being reconsidered - branchFromThought: If branching, which thought number is the branching point - branchId: Identifier for the current branch (if any) - needsMoreThoughts: If reaching end but realizing more thoughts needed You should: 1. Start with an initial estimate of needed thoughts, but be ready to adjust 2. Feel free to question or revise previous thoughts 3. Don't hesitate to add more thoughts if needed, even at the "end" 4. Express uncertainty when present 5. Mark thoughts that revise previous thinking or branch into new paths 6. Ignore information that is irrelevant to the current step 7. Generate a solution hypothesis when appropriate 8. Verify the hypothesis based on the Chain of Thought steps 9. Repeat the process until satisfied with the solution 10. Provide a single, ideally correct answer as the final output 11. Only set nextThoughtNeeded to false when truly done and a satisfactory answer is reached
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Tokenlab MCP Server
{
"mcpServers": {
"hedging8563-tokenlab-mcp-server": {
"command": "npx",
"args": [
"-y",
"@tokenlabai/mcp-server"
],
"env": {
"TOKENLAB_API_BASE": "YOUR_TOKENLAB_API_BASE_HERE",
"TOKENLAB_API_KEY": "YOUR_TOKENLAB_API_KEY_HERE",
"TOKENLAB_MCP_TOOL_PROFILE": "YOUR_TOKENLAB_MCP_TOOL_PROFILE_HERE",
"TOKENLAB_MCP_SCHEMA_MODE": "YOUR_TOKENLAB_MCP_SCHEMA_MODE_HERE",
"TOKENLAB_REQUEST_TIMEOUT_MS": "YOUR_TOKENLAB_REQUEST_TIMEOUT_MS_HERE",
"TOKENLAB_MCP_MAX_FILE_BYTES": "YOUR_TOKENLAB_MCP_MAX_FILE_BYTES_HERE",
"TOKENLAB_MCP_INLINE_BYTES": "YOUR_TOKENLAB_MCP_INLINE_BYTES_HERE",
"TOKENLAB_ARTIFACT_DIR": "YOUR_TOKENLAB_ARTIFACT_DIR_HERE"
}
}
}
}
Ncp
{
"mcpServers": {
"portel-dev-ncp": {
"command": "npx",
"args": [
"-y",
"@portel/ncp"
]
}
}
}
Frequently asked questions
Tokenlab MCP Server is categorized under Aggregators and uses a local stdio subprocess. Ncp belongs to Aggregators and uses a local stdio subprocess. Pick Tokenlab MCP Server for aggregators work and Ncp for aggregators.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Tokenlab MCP Server is listed as free. Auth: api key required. Ncp is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add hedging8563-tokenlab-mcp-server and portel-dev-ncp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Tokenlab MCP Server has a quality signal of 64/100 (Good) with 3 views, 0 installs and 1 GitHub stars. Ncp has 69/100 (Great) with 4 views, 0 installs and 100 GitHub stars.