web-research-mcp
The web-research-mcp server acts as a persistent, version-aware cache for web research, enabling host AI models to store, retrieve, and validate documentation without re-researching the same sources every session.
Browse the cache hierarchy: View a structured tree of cached technologies → versions → topics, including freshness flags, without fetching content.
Check freshness/existence: Quickly verify if a specific tech/topic reference is cached and current — returns status, staleness info, and slug without fetching full content.
Retrieve cached docs: Fetch complete markdown content for a cached reference by slug, or retrieve just a specific section/heading.
Full-text search: Search across topic names, summaries, content, and tags — optionally scoped to a specific technology.
Store new research: Save researched documentation (tech, topic, version, summary, content, tags, sources) into the cache; atomically supersedes older versions and warns about possible duplicate topics.
Invalidate references: Mark a cached entry as stale by slug, prompting re-research on next use.
Self-update guidance: Detect newer server versions on GitHub and return the update command, delegating execution to a background agent to avoid blocking workflow.
Enforce consultation (optional): Install a pre-edit hook requiring the host model to consult cached references before editing code for tracked technologies.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@web-research-mcpCheck if we have React server components documentation cached."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
web-research-mcp
An MCP server that keeps a persistent, version-aware cache of web research so the host model (Claude, Codex, …) writes modern, non-deprecated code without re-researching the same docs every session.
The server never browses the web itself — the host does the searching when the user asks. This server only stores what was found, answers "do we already have this? is it current?" cheaply, and serves the cached reference back.
Install
One line — no clone needed:
curl -LsSf https://raw.githubusercontent.com/jcsoftdev/web-research-mcp/main/install.sh | bashOr from a checkout:
./install.shInteractive: installs uv if missing, installs the web-research-mcp binary, then
asks which hosts to register into (Claude Code, Codex, Gemini, Claude Desktop,
Cursor) and wires each one up. The DB autocreates on first use.
Manual registration
# Claude Code
claude mcp add web-research -s user -- web-research-mcp
# Codex
codex mcp add web-research -- web-research-mcpOther hosts (JSON config):
{
"mcpServers": {
"web-research": { "command": "web-research-mcp", "args": [] }
}
}Related MCP server: claude-crowed
Tools
Tool | Cost | Behavior |
| minimal | Hierarchy tech → version → topics (names + |
| low |
|
| low | Loops |
| low-high | check + fetch in one round-trip; |
| low | Audits a full stack ( |
| med-high | Full markdown doc; optional section returns one heading block. |
| med | FTS5 over topic + summary + content + tags. |
| write | Stores a doc; atomically supersedes older versions (PEP 440 compare); rejects redundant saves over a fresh entry unless |
| write | Forces a reference stale. |
| minimal | Hit-rate, top missed techs (your research queue), estimated tokens saved by cache hits. |
Freshness is a structured field (status_tag, stale) placed first in every
response, and a stale entry carries an explicit advice field — the model can't
overlook deprecation buried in prose. A cache miss is a flat {"exists": false}.
Topic canonicalization
Known alias spellings of the same recurring topic (whats-new,
latest-changes, new-features, ...) are folded into one canonical topic
(latest-version) before a slug is built or looked up — in save_research,
check_reference, resolve_reference, check_reference_batch, and
get_reference (which also accepts an alias slug directly). This is
structural, not advisory: two hosts spelling the same topic differently
land on the same cache entry instead of forking it. The alias map is a static
seed (core/canonical.py); DB-backed, runtime-taught aliases are a deliberate
v2.
Dedup gate
save_research guards against forking the same concept under different topic
names (server-components vs servercomponents). Before inserting it looks for
similar existing topics for that tech and, if any, returns them in a
possible_duplicates field so the host reuses an existing slug instead of
creating a duplicate. It is advisory, non-blocking — unlike canonicalization,
above, it doesn't rewrite the topic, it only flags a candidate for the host to
reuse. Matching is lexical today (near-spellings, spacing, truncated
abbreviations); synonyms and non-truncation abbreviations (rsc vs
server-components) need embeddings, which swap in at the same call site via
EmbeddingProvider when EMBEDDINGS_ENABLED=1.
Enforcement hook (optional)
The MCP instructions only ask the model to call check_reference before
writing code or searching the web — nothing enforces it, and an ephemeral
subagent picked via tool-search never even sees the server's instructions
(only each tool's own description). The installer can wire host hooks that
turn the ask into a guarantee, at two points:
web-research-mcp hook --host {claude|codex|gemini|cursor}Pre-edit gate — if you are about to edit code for a cached tech and the
current session never consulted its reference, the edit is denied until
you do. Detects tracked techs via strong signals only (real JS/TS imports or
package.json dependency keys — never prose) and checks the session
transcript for a prior check_reference / get_reference call.
Search-redundancy gate (Claude Code only) — symmetric, for the other
direction: WebSearch / WebFetch is denied when the query/URL names a
tech that already has a fresh cached entry and it wasn't consulted this
session (call resolve_reference instead of re-researching). A PostToolUse
hook on the same tools injects a reminder to call save_research right after
a search completes — this fires for the main thread, Task-spawned
subagents, and Workflow agent() calls alike (all three verified empirically
to receive Claude Code hooks).
Detection is conservative by design in both gates: a false deny blocks legitimate work.
Install is opt-in (default no) because a deny is disruptive. Support:
host | event | status |
Claude Code |
| verified |
Codex |
| experimental |
Gemini CLI |
| experimental (schema unverified) |
Cursor |
| experimental |
The hook fails open: any parse error, unknown host, or unreadable DB allows the action — a bug in the gate must never wedge your editor.
Config (env vars)
var | default | purpose |
|
| DB location (global — reused across projects) |
|
| TTL for non-version-locked entries |
|
| vector search (post-MVP) |
|
| advertise updates so the host auto-delegates them; set |
Auto-update
The server never installs anything itself. It exposes a check_for_update tool
and, via its MCP instructions, asks the host to delegate a background agent to
run the update when a newer version exists on GitHub — so the update never blocks
you and takes effect on the next launch. The host does the work; the server only
detects and advises.
With WEB_RESEARCH_AUTO_UPDATE=0 the tool still exists but the instructions no
longer ask the host to auto-delegate — call check_for_update yourself when you
want it.
Develop
uv sync
uv run pytestMaintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseAqualityDmaintenanceProvides LLMs with up-to-date, version-specific documentation and code examples directly from library sources, eliminating outdated training data and hallucinated APIs by fetching current documentation at prompt time.Last updated21,139,612MIT
- AlicenseAqualityDmaintenanceA persistent semantic memory system for Claude Code that provides a structured, versioned document store with semantic search and graph visualization. It acts as a memoization layer to store and retrieve research, design decisions, and codebase insights across different work sessions.Last updated10Apache 2.0
- AlicenseAqualityDmaintenanceShared research cache for AI agents. Caches web research across sessions and users - hit means instant answer from verified sources, miss means your research saves the next dev's tokens. Semantic search with freshness tracking, gap detection, and real-time token measurement via JSONL. Free, open source.Last updated3359AGPL 3.0
- Alicense-qualityCmaintenanceProvides real-time, up-to-date documentation for major LLM providers (OpenAI, Anthropic, Google Gemini) to prevent hallucinations and outdated code patterns in AI agents.Last updated366MIT
Related MCP Connectors
Collaborative, cache-first web search for agents — cited answers from a shared live-web pool.
Token-efficient search for coding agents over public and private documentation.
Provide your AI coding tools with token-efficient access to up-to-date technical documentation for…
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/jcsoftdev/web-research-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server