Veda MCP
Enables AI apps to read Veda Knowledge Packs, offering source-aware context and tools for guided pack interaction.
README
Veda MCP
Veda MCP lets Claude, Cursor, Hermes, Codex, and other MCP-capable AI apps read Veda Knowledge Packs through a read-only MCP toolset.
Veda = AI-readable Knowledge Pack repository.
You ask inside your AI app; Veda supplies source-aware context through MCP.
Tools
This MCP exposes a guided Veda workflow plus read/update draft helpers:
| Tool | Purpose |
|---|---|
start_veda_session |
Start a guided flow: call, create, or update a Knowledge Pack. |
list_packs |
List Knowledge Packs allowed for your Veda MCP token. |
search_packs |
Search allowed Knowledge Packs. |
attach_pack_to_session |
Attach one Knowledge Pack as the active pack for the current AI conversation. |
get_pack_manifest |
Return pack structure, version, and file metadata. |
get_pack_sources |
Return source list for a pack. |
get_answer_policy |
Return pack-specific answer rules. |
get_pack_context_for_question |
Return compact, source-aware context from a selected pack for a user question. |
create_pack_draft |
Guide draft creation for a new Knowledge Pack. |
update_pack_draft |
Guide an update draft for an existing Knowledge Pack. |
report_pack_issue |
Report missing or wrong knowledge. |
Quick install by asking your AI
Copy this into the AI app you use for coding/automation:
Install this MCP server for me.
GitHub repository:
https://github.com/tman7162-star/veda-mcp
Use this command-based MCP server:
npx -y github:tman7162-star/veda-mcp
Environment variables:
VEDA_MCP_URL=https://veda.app/mcp
VEDA_MCP_TOKEN=<my Veda connection key here>
After installing, test it by listing my Veda Knowledge Packs.
Manual MCP config
Most MCP clients accept a config shape similar to this:
{
"mcpServers": {
"veda": {
"command": "npx",
"args": ["-y", "github:tman7162-star/veda-mcp"],
"env": {
"VEDA_MCP_URL": "https://veda.app/mcp",
"VEDA_MCP_TOKEN": "veda_mcp_xxxxxxxxxxxxxxxxxxxx"
}
}
}
}
For local development against a local Veda web app:
{
"mcpServers": {
"veda-local": {
"command": "node",
"args": ["C:/path/to/veda-mcp/src/index.js"],
"env": {
"VEDA_MCP_URL": "http://127.0.0.1:8795/mcp",
"VEDA_MCP_TOKEN": "veda_mcp_xxxxxxxxxxxxxxxxxxxx"
}
}
}
}
Environment variables
| Variable | Required | Default | Description |
|---|---|---|---|
VEDA_MCP_TOKEN |
yes | - | Veda connection key generated/approved from your Veda account. |
VEDA_MCP_URL |
no | https://veda.app/mcp |
Veda MCP endpoint. Use a local URL for local development. |
VEDA_TIMEOUT_MS |
no | 30000 |
Request timeout in milliseconds. |
Security notes
- Treat
VEDA_MCP_TOKENconnection key like a password. - Start with read-only scopes:
pack:readandpack:context. - If the token leaks, revoke/regenerate it in Veda.
- Do not paste your token into public GitHub issues, screenshots, or commits.
Development
npm install
npm run check
npm run smoke:list-tools
smoke:list-tools verifies that the local stdio MCP server can start and list its tool definitions. It does not require a valid Veda token because it does not call Veda tools.
License
MIT
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