CliDeck MCP — Network Knowledge
RemoteAbout CliDeck MCP — Network Knowledge
CliDeck MCP is an open-source, version-aware knowledge framework for AI agents working with network information. It serves source-backed answers through deterministic retrieval, marks unsupported questions as unknown, and supports research that publishes immutable revisions.
Key features
- 01Version-aware network knowledge retrieval
- 02Source-backed answers
- 03Explicit unknown results
- 04Research and revision publishing
- 05Domain-specific knowledge packs
Use cases
- 01Look up device commands and workflows
- 02Review upgrade and change information
- 03Research gaps in network knowledge
MCP support
It exposes network knowledge to clients through a Streamable HTTP MCP endpoint or a local server. Its tools cover device context, commands, workflows, snapshots, and topology; it provides guidance and does not connect to devices or execute commands.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.clideck.com/mcpclaude mcp add --transport http com-clideck-network-knowledge https://mcp.clideck.com/mcp{"mcpServers":{"com-clideck-network-knowledge":{"type":"http","url":"https://mcp.clideck.com/mcp"}}}Open in Cursor{"servers":{"com-clideck-network-knowledge":{"type":"http","url":"https://mcp.clideck.com/mcp"}}}Open in VS Code{"mcpServers":{"com-clideck-network-knowledge":{"type":"http","url":"https://mcp.clideck.com/mcp"}}}{"mcpServers":{"com-clideck-network-knowledge":{"serverUrl":"https://mcp.clideck.com/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
19| Parameter | Type | Required | Description |
|---|---|---|---|
| reason | string | Yes | |
| context | object | No | |
| context.model | string | No | |
| context.vendor | string | No | |
| context.version | string | No | |
| context.runtime_mode | string | No | |
| context.operating_system | string | No | |
| context.shell_environment | string | No | |
| question | string | Yes | |
| revision_refs | array | No |
Details
From the project READMECliDeck MCP
An open-source framework for version-aware, source-backed knowledge that AI agents query through MCP. Known answers use deterministic PostgreSQL retrieval; incomplete answers create durable research demands. Isolated Codex runs discover and extract evidence; the core validates and publishes immutable revisions. CliDeck provides guidance and never connects to devices or executes commands.
| Surface | URL |
|---|---|
| Public Streamable HTTP MCP | https://mcp.clideck.com/mcp |
| Network Evidence Workbench | https://mcp.clideck.com/webmcp |
| Live read-only operations demo | https://mcp.clideck.com/demo |
| Product page | https://clideck.com/software/mcp |
Capabilities
- Network Knowledge: device context, commands, workflows, snapshots and
redaction, change review, verification, upgrades, topology and expert tasks.
Exact context ranks first; broader guidance is labelled and unsupported
questions remain
unknown. Coverage varies by vendor, platform and version. - Domain Packs: subject-specific schemas and deterministic validation over the shared revision/release core. Engineering Measurements demonstrates exact decimal values, units and tolerances outside networking.
- Continuous research: 1–8 enabled isolated executors, independent Luna/High
models and official price comparison in
/admin/models; downloads, conversion, OCR, chunking, indexing and publication are mechanical. AI receives bounded tasks through the researcher bridge. See model policy. - WebMCP: six typed browser tools share a versioned case with the engineer. Complete files stay local; selected evidence is redacted before transmission. Browser-agent evidence access requires explicit opt-in. Manual controls work without WebMCP. See contract and walkthrough.
- Operations demo:
/adminand/demouse the same frontend and real production counters. Server-side projections redact private data; demo controls cannot mutate production.

Live totals are available in the demo and /public/v1/stats; historical counts
and test results are not current service guarantees. Codex was the primary
engineering environment. Pipeline use through a local authenticated Codex
installation needs no separate model API integration and remains subject to
plan and usage limits.
Run locally
Requirements: Node.js 24, pnpm as pinned in package.json, PostgreSQL 16
(Docker Compose is provided).
cp .env.example .env
set -a
source .env
set +a
pnpm install --frozen-lockfile
docker compose up -d postgres
pnpm db:migrate
pnpm db:seed
pnpm knowledge:reindex-applicability -- --resume --verify
pnpm build
pnpm dev:api
Edit .env for your local database before sourcing it. MCP listens at
http://127.0.0.1:8787/mcp. Worker/researcher entry points and all supported
commands are in package.json. Production uses the
canonical deployment workflow.
To connect the hosted service with the Codex CLI:
codex mcp add clideck --url https://mcp.clideck.com/mcp
codex mcp list
Other Streamable HTTP MCP clients can use the same endpoint.
Develop
pnpm check
pnpm test
pnpm eval
pnpm build
PostgreSQL integration tests and the 250-case evaluation need a migrated, seeded test database. A run that skips DB tests is not full release validation; the deploy script provisions its own disposable database and applies grants.
Create a pack:
pnpm domain:create -- --id marine-science --name "Marine Science"
pnpm install --lockfile-only
pnpm domain:validate -- --id marine-science
pnpm --filter @clideck/domain-marine-science test
See agent rules, documentation map, architecture, pack authoring and security.
License and privacy
Apache-2.0 covers code and project-authored fixtures, not production knowledge, third-party manuals or user data. Internal evidence and secrets stay private. The dedicated provenance tool exposes only allowlisted metadata for active revisions; the operations demo retains its stricter redaction boundary. See DATA-NOTICE.md.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.